···Ejercicio 1··· Carga de datos
load("C:/Users/Keiry/Documents/Eco22/modelo_ventas.RData")Calcule las matrices A, P, M
options(scipen = 99999999)
matriz_x <- model.matrix(modelo_ventas)
matriz_xx <- t(matriz_x) %*% matriz_x
#Matriz A
matriz_A <- solve(matriz_xx) %*% t(matriz_x)
head(matriz_A)## 1 2 3 4
## (Intercept) -0.01128647020 0.014103779728 0.03506391877 0.00042833810
## tv -0.00006704103 0.000030949142 -0.00061201930 -0.00021206420
## periodico 0.00139818182 -0.001907246902 -0.00254688165 0.00022932432
## radio -0.00058002134 0.000648666541 -0.00010932839 -0.00018997103
## tv:radio 0.00001481990 0.000001945347 0.00003260788 0.00001485919
## 5 6 7 8
## (Intercept) -0.02802264005 0.04966825571 0.006721406058 0.013685771163
## tv 0.00156830834 -0.00096215598 0.000111663780 -0.000326611039
## periodico 0.00023142788 -0.00327078177 -0.001147087178 0.000018738210
## radio 0.00061595623 -0.00033083611 0.000772490837 -0.000100744979
## tv:radio -0.00003937064 0.00004642785 -0.000008511094 0.000004091601
## 9 10 11 12
## (Intercept) 0.06237349027 0.019005753345 0.0190774881507 0.00360558894
## tv -0.00140215257 -0.000194663316 0.0000131809233 -0.00039756395
## periodico -0.00123590258 0.000225171010 -0.0005248899956 0.00094786986
## radio -0.00131344307 -0.000735913630 -0.0003341352189 -0.00006782492
## tv:radio 0.00004044251 0.000007159682 0.0000007922246 0.00000221642
## 13 14 15 16
## (Intercept) 0.014899113818 0.03634139729 -0.011844700457 -0.00371574112
## tv 0.000213286058 -0.00085844430 0.000196044767 -0.00048543648
## periodico -0.002038352833 -0.00023578263 0.000811932802 0.00097903989
## radio 0.000336815220 -0.00089476990 0.000067852348 -0.00029853987
## tv:radio 0.000005251734 0.00002304953 -0.000002557309 0.00002032708
## 17 18 19 20
## (Intercept) 0.01533281090 -0.01698619508 0.013579431193 0.003694513315
## tv 0.00003888414 -0.00013321239 -0.000102411708 -0.000053437811
## periodico -0.00123652539 0.00195099121 -0.000580428810 0.000138506238
## radio -0.00083378557 -0.00044690226 0.000145541883 0.000151937838
## tv:radio 0.00003057413 0.00001102821 -0.000000845325 -0.000003078161
## 21 22 23 24
## (Intercept) -0.015735702231 0.010614027039 0.0039565024 -0.001153283948
## tv 0.000494790312 -0.000052925056 0.0010010281 0.000090362439
## periodico 0.000793792331 0.000598233661 -0.0020168690 0.000758430507
## radio 0.000066848849 -0.000626475545 0.0008051669 -0.000180595683
## tv:radio -0.000008570347 0.000002653757 -0.0000242403 -0.000003687696
## 25 26 27 28
## (Intercept) 0.020932126859 0.017662003516 0.001906479731 0.000459166814
## tv -0.000212519874 -0.000294160295 -0.000060899474 -0.000027522912
## periodico -0.000575150168 0.000571758575 -0.000044632121 0.000892483305
## radio -0.000222315654 -0.000842174697 0.000474802108 -0.000270548547
## tv:radio 0.000004605371 0.000009579634 -0.000006627237 -0.000001017345
## 29 30 31 32
## (Intercept) -0.009229296933 -0.00074255704 -0.020737133237 -0.00169324433
## tv 0.000025600123 0.00064847607 0.000302455839 0.00053023898
## periodico 0.001140034360 -0.00063161328 0.001724818959 -0.00031085451
## radio 0.000072298919 0.00034965909 -0.000097870752 0.00025494172
## tv:radio -0.000005118001 -0.00001618543 -0.000006563958 -0.00001343427
## 33 34 35 36
## (Intercept) 0.008864197705 0.01027581678 0.04236431872 0.03033028408
## tv 0.000349355310 -0.00066871791 -0.00106304463 -0.00092566223
## periodico -0.000041683492 0.00119509517 0.00006961331 0.00082003595
## radio -0.000335141773 -0.00044960780 -0.00136411967 -0.00130298655
## tv:radio -0.000007465636 0.00001074002 0.00003137340 0.00002639173
## 37 38 39 40
## (Intercept) -0.03691371138 0.01189641422 0.008312017572 -0.016421791419
## tv 0.00035119573 -0.00034519692 0.000282477316 0.000055370346
## periodico 0.00199878941 -0.00124947589 -0.001302070784 0.001259943073
## radio 0.00110703560 0.00045954540 0.000562172245 0.000254407845
## tv:radio -0.00002740139 0.00001270793 -0.000008200132 -0.000004675563
## 41 42 43 44
## (Intercept) -0.007098668942 -0.006645942619 -0.007827522911 0.00562418953
## tv 0.000222581337 0.000155364334 -0.000299207325 0.00010847218
## periodico 0.000747334684 0.000268389768 0.001648736739 0.00051002693
## radio 0.000029797138 0.000282618270 0.000056961391 -0.00039368776
## tv:radio -0.000007123256 -0.000004170304 -0.000003001041 -0.00000234203
## 45 46 47 48
## (Intercept) 0.00884005605 -0.002874908479 0.00100977476 -0.02451539730
## tv 0.00046057305 0.000228756456 0.00056234506 0.00014158543
## periodico -0.00171033165 0.000265781998 -0.00025382772 0.00152356607
## radio 0.00063601703 0.000136973068 0.00008691167 0.00066324823
## tv:radio -0.00001057989 -0.000007309017 -0.00001413098 -0.00001407076
## 49 50 51 52
## (Intercept) -0.01878764724 0.00272615988 -0.00178738864 0.03598768964
## tv 0.00095991001 0.00058696509 0.00060244753 -0.00096600682
## periodico 0.00053544810 -0.00060557497 0.00034275541 -0.00005860236
## radio 0.00026402722 0.00021734621 -0.00018745312 -0.00090579432
## tv:radio -0.00002327068 -0.00001482293 -0.00001462919 0.00002476176
## 53 54 55 56
## (Intercept) -0.015681810129 0.00074396845 -0.011168389305 0.00002541883
## tv -0.000067159493 -0.00051349075 -0.000062236867 -0.00074494491
## periodico 0.001345269333 0.00072784252 0.001418155003 0.00125889173
## radio 0.000103698401 -0.00043431222 0.000114865241 -0.00068987402
## tv:radio 0.000001767024 0.00002405979 -0.000005442162 0.00003168547
## 57 58 59 60
## (Intercept) 0.01831083030 0.010653820682 -0.015790159420 -0.005853894390
## tv 0.00037974671 -0.000185452442 -0.000211903555 -0.000115582009
## periodico -0.00266494448 0.000025266826 0.001251591776 0.000891572787
## radio 0.00085114752 -0.000065272194 0.000267070291 0.000307153563
## tv:radio -0.00000890655 0.000001426743 0.000004245123 -0.000006380628
## 61 62 63 64
## (Intercept) 0.024987561800 -0.01302879544 -0.002445181178 0.004949872745
## tv -0.000173057706 -0.00028160660 0.000128664831 -0.000096027177
## periodico -0.000434643049 0.00173643412 0.000887450274 -0.000331339214
## radio -0.000610378781 -0.00043427213 -0.000232545627 0.000581957346
## tv:radio 0.000006783625 0.00001501912 -0.000004268503 -0.000007163908
## 65 66 67 68
## (Intercept) -0.00821712853 0.04273553577 0.0229473149842 0.01820829672
## tv 0.00006580937 -0.00110033999 -0.0003618915503 -0.00052137470
## periodico 0.00001079112 -0.00041586509 -0.0012710528427 0.00037421605
## radio 0.00072776383 -0.00093213639 0.0004476366163 -0.00050459832
## tv:radio -0.00000712428 0.00002837397 0.0000006298279 0.00001117128
## 69 70 71 72
## (Intercept) -0.00587330896 -0.019410327467 -0.010929740347 0.001720050399
## tv -0.00015525538 0.000059280863 0.000208663285 0.000322859874
## periodico 0.00114264022 0.001140588393 0.000751392556 0.000022233140
## radio 0.00012267595 0.000570942606 0.000152655637 0.000009188374
## tv:radio -0.00000395234 -0.000008096259 -0.000005496981 -0.000008621258
## 73 74 75 76
## (Intercept) 0.014155913033 0.004183081585 0.000096498081 0.04133114660
## tv 0.000108055467 0.000387042857 -0.000182478045 -0.00071691915
## periodico -0.001983762315 0.000107969277 0.000778771733 -0.00259939839
## radio 0.001013932711 -0.000213930377 0.000032463947 -0.00064778051
## tv:radio -0.000009976884 -0.000009149524 -0.000001450933 0.00004497655
## 77 78 79 80
## (Intercept) 0.029052219752 0.004019870279 0.02568587940 0.014215520541
## tv -0.000213088043 -0.000054586137 -0.00002185503 -0.000049182026
## periodico -0.000740382123 -0.000223275356 -0.00276030449 0.000039133548
## radio -0.000591894264 0.000460017434 0.00111509664 -0.000423521968
## tv:radio 0.000008015092 -0.000005969221 -0.00000879480 0.000001929415
## 81 82 83 84
## (Intercept) 0.008345104731 -0.0067821677 0.004921867503 0.005786401831
## tv 0.000056112718 0.0007153471 0.000298223994 -0.000016296534
## periodico -0.000802770542 0.0005249677 -0.000613853773 -0.001299317483
## radio 0.000474863427 -0.0001189448 0.000286351652 0.000828294453
## tv:radio -0.000005880627 -0.0000177861 -0.000008593964 -0.000001622635
## 85 86 87 88
## (Intercept) -0.015196826163 -0.02826803967 0.009478256801 0.00697422257
## tv -0.000019107862 0.00135194466 -0.000035948293 -0.00019524819
## periodico 0.001025333548 0.00045642150 -0.000779061930 -0.00042841743
## radio 0.000362986505 0.00046608800 0.000520009708 -0.00015610155
## tv:radio -0.000002475481 -0.00003065541 -0.000005520579 0.00001652708
## 89 90 91 92
## (Intercept) -0.01345947077 0.00933095016 0.0324700557 0.01006201929
## tv 0.00101277100 -0.00042350545 -0.0008446069 0.00055051470
## periodico -0.00055310023 -0.00060621191 0.0003259917 -0.00069641935
## radio 0.00040642574 0.00009972553 -0.0011152082 -0.00006211493
## tv:radio -0.00001719827 0.00001793239 0.0000238975 -0.00001293978
## 93 94 95 96
## (Intercept) -0.012561667584 -0.01359268266 0.0226058265 -0.008511490317
## tv 0.000232457597 0.00002954089 -0.0004968032 0.000309545708
## periodico 0.000875090545 0.00148757677 -0.0001259276 0.000288419189
## radio -0.000128556632 -0.00059940482 -0.0004127950 0.000113139890
## tv:radio 0.000001429484 0.00001306496 0.0000108430 -0.000003180198
## 97 98 99 100
## (Intercept) 0.03711720155 0.000973109872 -0.01776733122 -0.000306931148
## tv -0.00109143130 -0.000019982349 -0.00022920641 -0.000098468643
## periodico 0.00056483304 0.000543224560 0.00208921866 -0.000150663149
## radio -0.00139218359 -0.000039807925 -0.00039761456 0.000243435856
## tv:radio 0.00003115892 -0.000002490315 0.00001179114 0.000005777537
## 101 102 103 104
## (Intercept) -0.0225338310 -0.01477602943 0.006267206369 0.007047657756
## tv 0.0014546750 0.00002311872 -0.000136410903 -0.000186875718
## periodico 0.0002772215 0.00191700120 0.000964993794 0.000550081239
## radio 0.0004411293 -0.00122375976 -0.000580253503 -0.000256494905
## tv:radio -0.0000376632 0.00002504818 0.000003477592 0.000002322845
## 105 106 107 108
## (Intercept) -0.015584348939 0.00606196517 0.015896337611 0.021292700367
## tv 0.000008587482 -0.00051842974 0.000293954503 -0.000076845097
## periodico 0.001254319136 0.00016389592 -0.001228173794 -0.000183639474
## radio 0.000591893676 -0.00032987456 0.000150658879 -0.000650144117
## tv:radio -0.000013381956 0.00002443714 -0.000007469916 0.000004553308
## 109 110 111 112
## (Intercept) 0.0259081117932 -0.005860740324 -0.03061336840 -0.018733131894
## tv 0.0000990139053 -0.000268584134 0.00161850702 0.000081711294
## periodico -0.0011455106749 0.001438677829 0.00051166319 0.001331666756
## radio -0.0003291803759 0.000033869706 0.00056348576 0.000439565172
## tv:radio -0.0000002575464 -0.000002297405 -0.00004137368 -0.000009291272
## 113 114 115 116
## (Intercept) 0.02231473162 0.006912749678 0.00350450818 0.0057889554831
## tv -0.00078956888 -0.000340935519 -0.00003798319 0.0001746561394
## periodico 0.00054611658 0.000711647822 -0.00114787787 -0.0010782704889
## radio -0.00063433762 -0.000199410936 0.00087218898 0.0003540656623
## tv:radio 0.00001686494 0.000003836647 -0.00000186540 0.0000009186797
## 117 118 119 120
## (Intercept) 0.007621528529 0.03207311114 0.00348876480 0.023749714363
## tv 0.000084597739 -0.00061246798 0.00002447478 0.000002781209
## periodico -0.000008596092 0.00003257176 -0.00028204609 -0.001641919181
## radio -0.000112009007 -0.00105955721 -0.00037873008 0.000235882012
## tv:radio -0.000003007049 0.00001919778 0.00001640435 -0.000001574375
## 121 122 123 124
## (Intercept) -0.008371458679 0.00579076808 0.0246214091 -0.00227449922
## tv 0.000433253314 0.00077346417 -0.0005429257 0.00007232554
## periodico 0.000163710546 -0.00193425007 0.0005456834 -0.00029428162
## radio 0.000230048851 0.00073326798 -0.0010511815 0.00083239722
## tv:radio -0.000009110407 -0.00001741039 0.0000166963 -0.00001233571
## 125 126 127 128
## (Intercept) -0.016078222443 0.011484301170 0.024292095391 0.04260889135
## tv 0.000403387727 0.000102516148 0.000039115008 -0.00099042499
## periodico 0.000997828788 -0.000313829344 -0.002941077130 -0.00005357818
## radio -0.000299975517 -0.000121803519 0.000741096734 -0.00134594321
## tv:radio 0.000002109399 -0.000002888536 0.000004259761 0.00002996835
## 129 130 131 132
## (Intercept) -0.04184894876 -0.00340210494 0.02635875495 -0.01680636474
## tv 0.00060133947 0.00085499383 0.00030830294 0.00110001765
## periodico 0.00149779495 -0.00064927980 -0.00434810562 0.00066593110
## radio 0.00165705121 0.00038887607 0.00208020059 0.00008961022
## tv:radio -0.00003768111 -0.00002141744 -0.00002206911 -0.00002816220
## 133 134 135 136
## (Intercept) 0.02919608430 -0.012799174302 0.01695419897 -0.00456404857
## tv -0.00022524016 0.000167341441 -0.00004276786 0.00049170331
## periodico -0.00247706077 0.000947591304 -0.00176944627 -0.00200884389
## radio 0.00090330909 0.000048936950 0.00014621124 0.00205837354
## tv:radio -0.00000435789 -0.000002109586 0.00001305045 -0.00003052679
## 137 138 139 140
## (Intercept) 0.00778594521 -0.022596153125 0.014558760948 -0.02706944785
## tv 0.00023732597 0.000501127883 0.000030221347 0.00043062493
## periodico -0.00212530270 0.001495386134 -0.001362977777 0.00069016250
## radio 0.00155063090 -0.000139327979 0.000563911227 0.00150299208
## tv:radio -0.00001977492 -0.000006599755 -0.000005442513 -0.00003119953
## 141 142 143 144
## (Intercept) 0.020217704051 -0.0082726940 -0.014022424717 0.00168474054
## tv -0.000338761324 0.0001422678 0.000137252931 0.00056054532
## periodico -0.000472916959 0.0007072714 0.001111115544 -0.00007458885
## radio -0.000126687558 -0.0004324584 0.000110590807 -0.00006142670
## tv:radio 0.000005712816 0.0000109961 -0.000004031128 -0.00001374589
## 145 146 147 148
## (Intercept) -0.00198829800 0.03763194326 0.02629464036 -0.01543522339
## tv 0.00060063272 -0.00095187216 -0.00081254970 -0.00036412185
## periodico -0.00031062935 0.00025268846 0.00074360036 0.00173390852
## radio 0.00023599016 -0.00130077426 -0.00107440049 -0.00012045260
## tv:radio -0.00001515365 0.00002809328 0.00002194616 0.00001218465
## 149 150 151 152
## (Intercept) 0.00403254897 0.013338479273 -0.01215692775 -0.01696418130
## tv 0.00024965446 0.000027895532 0.00051576139 0.00122943937
## periodico -0.00181365109 -0.001219077194 0.00104733986 0.00004097211
## radio 0.00149714575 0.000528800275 -0.00010471182 0.00041295892
## tv:radio -0.00001947075 -0.000005332999 -0.00001315815 -0.00003126069
## 153 154 155 156
## (Intercept) 0.001417534822 -0.008470399675 0.007947807307 0.04992101740
## tv -0.000186653453 0.000013929832 -0.000357034184 -0.00074406765
## periodico 0.000739771135 0.000456080437 0.000603260782 -0.00226306936
## radio -0.000026698877 0.000326717452 -0.000156384232 -0.00023230271
## tv:radio -0.000000566054 -0.000001153531 0.000003807189 0.00001812879
## 157 158 159 160
## (Intercept) 0.00778287975 0.016044205762 0.0198020921866 -0.00083849089
## tv -0.00021113564 -0.000010068402 0.0001294379729 0.00037522400
## periodico -0.00077083109 0.000141570665 -0.0026390976690 -0.00007396010
## radio 0.00022254888 -0.000633397205 0.0008090011419 0.00015964400
## tv:radio 0.00001127609 0.000002441521 -0.0000006920975 -0.00001006745
## 161 162 163 164
## (Intercept) -0.001790463491 0.0046878588293 0.000641191193 -0.0113002582
## tv 0.000243976491 0.0001313245628 0.000075684680 0.0001188405
## periodico 0.000371379207 -0.0009227419417 0.000527587196 0.0003582426
## radio 0.000004212692 0.0003693030404 -0.000100996155 0.0009174504
## tv:radio -0.000007238300 0.0000007849008 -0.000003640183 -0.0000166088
## 165 166 167 168
## (Intercept) 0.02587324499 -0.07225833746 0.01468504348 0.016653514998
## tv -0.00069122946 0.00355381404 0.00016799347 -0.000278836159
## periodico -0.00003379496 0.00018304394 -0.00246725793 0.000531485509
## radio -0.00050191766 0.00189664307 0.00127380853 -0.000762066393
## tv:radio 0.00001503164 -0.00009459444 -0.00001194893 0.000008659777
## 169 170 171 172
## (Intercept) -0.0202275264 0.02145995752 0.024433979551 -0.01151738746
## tv 0.0007922543 -0.00082193713 -0.000215338084 0.00067982384
## periodico 0.0007450594 0.00106072925 -0.000878903608 0.00019398865
## radio 0.0001652481 -0.00099540350 -0.000200975390 0.00025915032
## tv:radio -0.0000160912 0.00002053574 0.000005026328 -0.00001576635
## 173 174 175 176
## (Intercept) 0.0235756400961 0.02514494140 0.02775837039 -0.021103947078
## tv -0.0001232980468 -0.00059562607 -0.00066961037 -0.000312707438
## periodico -0.0015784204846 0.00031894679 0.00047486399 0.002179846329
## radio 0.0003275548165 -0.00085657634 -0.00108649690 -0.000111475421
## tv:radio -0.0000003579651 0.00001637958 0.00001978627 0.000009318024
## 177 178 179 180
## (Intercept) -0.01266987581 -0.00181364734 0.012597917565 0.015766611551
## tv 0.00001151397 0.00056422607 -0.000052667635 -0.000302612184
## periodico 0.00133066382 0.00016722575 0.000560014361 0.000378948165
## radio 0.00016996396 -0.00005098358 -0.000713286259 -0.000567858400
## tv:radio -0.00000642050 -0.00001404644 0.000003337299 0.000007731302
## 181 182 183 184
## (Intercept) 0.0375360999 0.006249894866 0.01182661003 -0.01048364001
## tv -0.0009729864 0.000166421440 0.00031343971 -0.00052366780
## periodico 0.0002714128 0.000477573166 -0.00052064220 0.00227758259
## radio -0.0012900129 -0.000444787514 -0.00013754438 -0.00108855870
## tv:radio 0.0000283698 -0.000003254349 -0.00000715736 0.00003015597
## 185 186 187 188
## (Intercept) -0.00878542694 -0.02403900996 0.012112048659 -0.004594159372
## tv 0.00018271141 0.00018060293 0.000133139885 -0.000015963520
## periodico 0.00108395802 0.00115362937 0.000138903045 0.000616178833
## radio -0.00007791804 0.00087000126 -0.000505287750 0.000269956649
## tv:radio -0.00000628598 -0.00001563611 -0.000001664489 -0.000005867028
## 189 190 191 192
## (Intercept) 0.01849130882 0.0234202371995 0.00170359876 0.03410061697
## tv -0.00081441237 0.0000187047846 0.00032730615 -0.00080167299
## periodico 0.00112799685 -0.0013998890588 -0.00188675507 -0.00036176657
## radio -0.00084391921 0.0000586567527 0.00172810634 -0.00068749942
## tv:radio 0.00001843973 -0.0000008807575 -0.00002479561 0.00001995866
## 193 194 195 196
## (Intercept) 0.01595370696 -0.02143366996 -0.00858635415 0.03609474671
## tv 0.00044877998 0.00033114925 0.00008016567 -0.00059753273
## periodico -0.00121850007 0.00049794605 0.00023567381 -0.00062652493
## radio 0.00004599813 0.00134310708 0.00088908809 -0.00080528477
## tv:radio -0.00001048754 -0.00002656952 -0.00001558263 0.00001780196
## 197 198 199 200
## (Intercept) 0.03769835435 0.02808613397 -0.01282058462 0.0246735133
## tv -0.00090291732 -0.00085615088 -0.00037778479 -0.0007715129
## periodico -0.00008300596 0.00052741693 0.00213262423 0.0007233832
## radio -0.00107306292 -0.00096939133 -0.00084263918 -0.0009870685
## tv:radio 0.00002548349 0.00002210282 0.00002311277 0.0000202718#Matriz P
matriz_P <- matriz_x %*% matriz_A
head(matriz_P)## 1 2 3 4 5 6
## 1 0.031814594 0.0037034602 0.01758786 0.022508722 0.0059178537 0.01974129
## 2 0.003703460 0.0246048049 0.03447285 0.012120221 -0.0004597074 0.04154714
## 3 0.017587861 0.0344728495 0.06766822 0.026410473 -0.0141470892 0.08506815
## 4 0.022508722 0.0121202208 0.02641047 0.020319815 -0.0016776287 0.03138114
## 5 0.005917854 -0.0004597074 -0.01414709 -0.001677629 0.0483724641 -0.02300480
## 6 0.019741287 0.0415471420 0.08506815 0.031381139 -0.0230047960 0.10805317
## 7 8 9 10 11
## 1 -0.003964913 -0.0016071128 -0.0058291615 0.001421804 -0.002168503
## 2 0.015101307 0.0024432890 0.0063462287 -0.003663155 0.002485740
## 3 0.012176441 -0.0003834528 0.0220657545 -0.003394744 0.002292606
## 4 0.003373267 0.0006504267 0.0009492958 -0.001311471 -0.001747623
## 5 0.001419930 -0.0036539819 -0.0241326482 0.007110009 0.009967185
## 6 0.013397526 -0.0005956252 0.0324090899 -0.003700809 0.002853121
## 12 13 14 15 16 17
## 1 0.0002759271 0.011079803 -0.0018040194 0.015540826 0.026214803 0.03915388
## 2 -0.0032037695 0.025864615 0.0008626337 0.003574967 0.008868805 0.02564936
## 3 -0.0111934245 0.042888059 0.0069060350 0.004272134 0.022703414 0.06550938
## 4 0.0004375016 0.016265742 0.0004952366 0.011268392 0.022780018 0.03416510
## 5 -0.0067191936 0.008010246 -0.0119590637 0.009198107 -0.009839149 0.01193130
## 6 -0.0145749642 0.051950428 0.0110403269 0.002643624 0.026876592 0.08070465
## 18 19 20 21 22
## 1 0.028866660 -0.0030446199 0.000749125 0.016155514 0.0034333941
## 2 -0.000720293 0.0071457201 0.003240265 0.002271601 -0.0054681525
## 3 0.006492895 0.0050758153 -0.001537902 0.001742739 -0.0078040763
## 4 0.019501862 0.0008189455 0.001968809 0.009949161 -0.0008765953
## 5 0.002531157 0.0011497447 0.002059947 0.018716452 0.0101482600
## 6 0.005662454 0.0057362342 -0.003175472 -0.001073962 -0.0099500685
## 23 24 25 26 27
## 1 -0.004316663 0.005388466 -0.0028420546 0.003165795 -0.002681876
## 2 0.016806251 -0.002823854 0.0047916106 -0.005776572 0.005609148
## 3 0.014422778 -0.007857187 0.0053003997 -0.005590199 -0.002015896
## 4 -0.000107821 0.001795623 -0.0001953947 -0.000605781 0.001115757
## 5 0.029805892 0.009631299 0.0016052193 0.004805308 -0.001277872
## 6 0.014983505 -0.011271156 0.0068710163 -0.006332393 -0.004069901
## 28 29 30 31 32
## 1 0.005390598 0.007082428 0.0010532517 0.017442057 0.0026253735
## 2 -0.003936020 -0.002448325 0.0069889995 -0.004638734 0.0051955492
## 3 -0.008802296 -0.009814065 0.0028884407 -0.009107492 0.0011305214
## 4 0.001728407 0.003979545 0.0008445642 0.008964771 0.0016461471
## 5 0.006801279 0.004524996 0.0225484790 0.013979429 0.0195427955
## 6 -0.012140107 -0.014335892 0.0010838046 -0.014493445 -0.0009670167
## 33 34 35 36 37
## 1 -0.00007829225 0.0015102737 0.0008416577 0.0041787942 0.0017327653
## 2 -0.00221677583 -0.0060880287 -0.0028577552 -0.0073185847 -0.0053479204
## 3 -0.00644336221 -0.0114263483 0.0065243581 -0.0020501923 -0.0303344305
## 4 -0.00334836745 0.0006446965 0.0009256259 0.0013001052 0.0001262853
## 5 0.02040057341 -0.0114424018 -0.0137641346 -0.0105763886 0.0040538823
## 6 -0.00900292961 -0.0138701490 0.0114936966 -0.0001144943 -0.0425433040
## 38 39 40 41 42
## 1 0.01100707 -0.001115782 0.0126410441 0.0073136600 0.009811140
## 2 0.02391753 0.015069418 0.0008899392 -0.0007424149 0.006867569
## 3 0.03786954 0.015498591 -0.0040621941 -0.0060140321 0.006323815
## 4 0.01826930 0.004154417 0.0093369705 0.0037685103 0.009004553
## 5 -0.01140309 0.008911453 0.0028637360 0.0113697277 0.006311546
## 6 0.04608851 0.017539147 -0.0079045093 -0.0096917200 0.005464233
## 43 44 45 46 47
## 1 0.0022075484 0.0033944730 -0.0007196211 0.004887768 0.000636477
## 2 -0.0072554645 -0.0038024488 0.0180678107 0.002634461 0.002101190
## 3 -0.0201607339 -0.0076354001 0.0203916189 -0.001512283 -0.003339865
## 4 0.0002723174 -0.0005124565 0.0048484101 0.003422348 -0.001340547
## 5 -0.0053101606 0.0128093190 0.0138702814 0.010782422 0.022602305
## 6 -0.0266180754 -0.0104089307 0.0233681422 -0.003912381 -0.006217283
## 48 49 50 51 52
## 1 0.007218179 0.0085812388 -0.0005966116 0.002124699 -0.0016233017
## 2 -0.001158588 -0.0007964303 0.0051694004 -0.004348470 0.0001020848
## 3 -0.014848525 -0.0091883803 0.0005973611 -0.011987797 0.0056863913
## 4 0.005349817 0.0019540716 -0.0009760684 -0.003289900 0.0008084888
## 5 0.001695566 0.0323525873 0.0221912225 0.026565676 -0.0153479213
## 6 -0.022098485 -0.0153734645 -0.0013464757 -0.016954994 0.0096356490
## 53 54 55 56 57
## 1 0.01794311515 0.027813359 0.005972562 0.033101095 -0.005429990
## 2 0.00248737108 0.010730919 -0.004358107 0.008569113 0.025385846
## 3 0.00255547165 0.028524124 -0.014331057 0.029230585 0.030580388
## 4 0.01382880419 0.024362404 0.003022021 0.027797530 0.004858263
## 5 -0.00001551011 -0.009370305 0.001299242 -0.014705638 0.009685108
## 6 0.00051857897 0.034474036 -0.019967656 0.035690206 0.036560576
## 58 59 60 61 62
## 1 -0.0003563637 0.018405772 0.0007718026 -0.0019216266 0.028730158
## 2 0.0025162950 0.005689590 -0.0010323673 0.0006979854 0.001883112
## 3 -0.0004207625 0.006926438 -0.0117697000 0.0025139247 0.011445493
## 4 0.0010236294 0.016254362 0.0011481807 -0.0019962776 0.020972764
## 5 0.0003442756 -0.006457950 -0.0018097259 0.0069605734 -0.002291898
## 6 -0.0010324225 0.005957259 -0.0164843646 0.0039102251 0.012199763
## 63 64 65 66 67
## 1 0.006115473 -0.00575888212 0.0054494293 -0.0036138722 -0.011617705
## 2 -0.004117580 0.00734651661 0.0108369324 0.0024431192 0.012115501
## 3 -0.009526818 -0.00086188472 0.0071867691 0.0100832760 0.008597360
## 4 0.001582491 -0.00007101528 0.0086763845 0.0007278373 -0.001728730
## 5 0.011313231 -0.00316567129 -0.0008682326 -0.0190600226 -0.009352013
## 6 -0.013431892 -0.00245372803 0.0062556242 0.0156958702 0.010853193
## 68 69 70 71 72
## 1 0.0005469009 0.002934147 0.0103026731 0.0115071337 0.0023494857
## 2 -0.0014442658 -0.003175949 0.0032133517 0.0025518083 0.0015927828
## 3 -0.0020694491 -0.012947005 -0.0042415718 0.0000402868 -0.0027003456
## 4 0.0007813228 0.001700562 0.0091774525 0.0082015202 0.0005687564
## 5 -0.0058163138 -0.001368084 -0.0001750268 0.0091307843 0.0155235094
## 6 -0.0019046559 -0.017786805 -0.0085259610 -0.0025652860 -0.0050745314
## 73 74 75 76 77
## 1 -0.0099782744 0.001333042 0.002111718 0.02743539 -0.003463964
## 2 0.0205623129 -0.001862759 -0.001329879 0.03622436 0.002686720
## 3 0.0179995065 -0.006913584 -0.008431787 0.08080567 0.005726683
## 4 0.0015483245 -0.002118511 0.001664044 0.03321476 -0.002190870
## 5 -0.0004663288 0.020097952 -0.001078586 -0.01269759 0.005719769
## 6 0.0209680704 -0.010028399 -0.011716008 0.10212156 0.008191585
## 78 79 80 81 82
## 1 -0.0029172672 -0.017683650 0.0007147327 -0.002945595 0.003301367
## 2 0.0067346299 0.024228182 -0.0008202598 0.010766108 -0.005259489
## 3 0.0002880732 0.021708315 -0.0021312910 0.007858672 -0.014361239
## 4 0.0012727699 -0.001853458 -0.0007675508 0.002180415 -0.003106977
## 5 -0.0008449312 -0.004702395 0.0084909965 0.002685843 0.029263537
## 6 -0.0010789394 0.026445857 -0.0028254636 0.008427233 -0.020398275
## 83 84 85 86 87
## 1 0.0003371442 0.003008872 0.0133864079 0.012804381 -0.0050107774
## 2 0.0080091104 0.021214491 0.0044826317 0.001434141 0.0104062858
## 3 0.0056872082 0.025430724 0.0018014995 -0.006450985 0.0060499645
## 4 0.0020745524 0.011083875 0.0116644922 0.004448956 0.0011010411
## 5 0.0120916478 -0.004004360 -0.0007270034 0.042272137 -0.0005368574
## 6 0.0053531520 0.029761661 -0.0005762994 -0.013222963 0.0063546389
## 88 89 90 91 92 93
## 1 0.021325247 0.01477712 0.01730354 0.0015829227 -0.003428544 0.021743646
## 2 0.016871282 0.01195406 0.01962937 -0.0037024430 0.002271494 0.004504497
## 3 0.034864659 0.01553121 0.03596225 0.0017972966 -0.002274857 0.010332240
## 4 0.021109728 0.01078879 0.02078517 0.0007708485 -0.004445140 0.015370593
## 5 -0.001216796 0.03209347 -0.01083455 -0.0096213148 0.024396046 0.011815717
## 6 0.042225687 0.01531560 0.04384692 0.0045820694 -0.004157674 0.010129518
## 94 95 96 97 98 99
## 1 0.032844286 -0.0017969091 0.015241189 0.002952671 0.0035767892 0.028356283
## 2 0.002810524 0.0018859775 0.007258299 -0.005717905 -0.0002569184 -0.001103946
## 3 0.016334217 0.0025491337 0.010699649 0.001945193 -0.0051082293 0.005033977
## 4 0.022465802 0.0003619854 0.011921848 0.001502198 0.0021930049 0.019541145
## 5 0.009089004 -0.0056512310 0.012502683 -0.014719072 0.0048131207 -0.001059394
## 6 0.017938274 0.0040199493 0.010650219 0.005524197 -0.0076941858 0.003885221
## 100 101 102 103 104
## 1 0.013863910 0.002413055 0.048451432 0.0053168995 0.002653151
## 2 0.013492546 -0.003463899 0.002505832 -0.0064891634 -0.001622762
## 3 0.021019326 -0.018700619 0.028158653 -0.0097834932 -0.005171523
## 4 0.015158105 -0.005084294 0.032017325 0.0005771213 0.001310801
## 5 -0.001727939 0.047004605 0.013885205 0.0066758788 0.001925084
## 6 0.024316278 -0.027995795 0.032782646 -0.0126359821 -0.007031004
## 105 106 107 108 109
## 1 0.00009995288 0.02526116 -0.004749254 -0.0007485001 -0.005672610
## 2 -0.00260929368 0.01473435 0.009061668 -0.0015631086 0.005067056
## 3 -0.01872241182 0.03424913 0.007999778 -0.0010986470 0.006187925
## 4 0.00023665627 0.02418343 -0.001454019 -0.0024500010 -0.003708917
## 5 -0.00094993885 -0.01024973 0.014135529 0.0102863033 0.013195848
## 6 -0.02604391369 0.04185212 0.009071375 -0.0008856774 0.008045006
## 110 111 112 113 114
## 1 0.0026188337 0.005771231 0.0086629510 -0.0001175903 0.001545444
## 2 -0.0057525446 -0.003484357 -0.0003918361 -0.0026527589 -0.002098966
## 3 -0.0168470426 -0.019432650 -0.0100643251 -0.0027944289 -0.007044843
## 4 0.0008908024 -0.003153845 0.0063886779 0.0007764986 0.001167366
## 5 -0.0040703359 0.050498338 0.0021044217 -0.0129649799 -0.003551416
## 6 -0.0224155724 -0.029724867 -0.0155977870 -0.0021378444 -0.009213841
## 115 116 117 118 119 120
## 1 0.003597274 0.009832110 0.0011860601 0.0005756822 0.027543034 -0.007546088
## 2 0.020824272 0.017995010 0.0016157498 -0.0028243277 0.015850759 0.013278881
## 3 0.024296887 0.027038525 -0.0013020365 0.0023639602 0.037358217 0.014491705
## 4 0.011561255 0.012900823 0.0005203164 -0.0005306074 0.023694853 -0.000524932
## 5 -0.005278239 0.006482524 0.0093448438 -0.0026096379 0.007535961 0.004285915
## 6 0.028199734 0.031807687 -0.0026011247 0.0049680355 0.044936677 0.017897096
## 121 122 123 124 125
## 1 0.010092883 -0.001256304 0.0030494045 -0.0045758255 0.028066830
## 2 0.005764217 0.018516539 -0.0059078442 0.0087758902 0.004441707
## 3 0.004755727 0.019680129 -0.0030689587 -0.0010304012 0.014097201
## 4 0.007492325 0.003474396 -0.0001193038 0.0010866591 0.018687216
## 5 0.015780813 0.022947464 -0.0008682083 -0.0006374068 0.018442316
## 6 0.003138228 0.021878187 -0.0023381941 -0.0035058869 0.014427641
## 126 127 128 129 130
## 1 -0.0005171007 0.001157018 0.0004007523 -0.0030631966 0.00009101935
## 2 0.0029373475 0.032144210 -0.0023952609 -0.0008164906 0.00572752482
## 3 0.0008912172 0.047216834 0.0070207827 -0.0300466960 -0.00046601269
## 4 -0.0003336806 0.013069487 0.0004954016 -0.0015646169 -0.00108166432
## 5 0.0102855100 -0.000672922 -0.0115576380 0.0067207540 0.02884527971
## 6 0.0003635419 0.057912269 0.0120335412 -0.0431300359 -0.00348480049
## 131 132 133 134 135 136
## 1 -0.027495731 0.003753654 -0.018387688 0.016054268 0.014553526 -0.016977864
## 2 0.037678848 -0.006663725 0.021052314 0.002787004 0.025500235 0.023507277
## 3 0.032569001 -0.019849158 0.018150282 0.003146075 0.045757412 0.008206339
## 4 -0.003453268 -0.004475979 -0.003028304 0.011444971 0.019286583 -0.001706439
## 5 -0.003180179 0.039230507 -0.008904895 0.008395455 0.001440959 0.001213916
## 6 0.038958460 -0.028413252 0.022657489 0.001230203 0.056018846 0.006547489
## 137 138 139 140 141 142
## 1 -0.015872880 0.022599957 -0.006392195 -0.006815004 -0.003521477 0.029619162
## 2 0.022276334 -0.001616463 0.014262012 0.003298025 0.005167978 0.007993406
## 3 0.012739833 -0.001349017 0.012549005 -0.021062955 0.004700184 0.023291407
## 4 -0.001384722 0.012684888 0.001251770 -0.002415945 0.000221457 0.021841085
## 5 -0.001496246 0.020292857 0.001398814 0.003536289 -0.003431624 0.011424455
## 6 0.013584550 -0.005262522 0.014626764 -0.030731387 0.006162335 0.026670719
## 143 144 145 146 147
## 1 0.013667000 0.0005481730 0.0019927013 0.001662813 0.003293329
## 2 0.000924610 -0.0005880946 0.0042853267 -0.003996589 -0.005943807
## 3 -0.001923799 -0.0067065339 -0.0006231371 0.003672735 -0.002606658
## 4 0.009390502 -0.0026509430 0.0005364973 0.000774948 0.001167379
## 5 0.006978404 0.0241251723 0.0220725196 -0.011027079 -0.009327458
## 6 -0.005104696 -0.0102282337 -0.0032134578 0.007485127 -0.001343292
## 148 149 150 151 152
## 1 0.025005933 -0.0131117591 -0.005633951 0.008303315 0.0028578847
## 2 0.003038181 0.0207572750 0.013247648 -0.005440820 -0.0002684596
## 3 0.008685493 0.0112517037 0.011242578 -0.013335024 -0.0118643771
## 4 0.019804986 -0.0001254037 0.001372099 0.001275566 -0.0027561870
## 5 -0.007948305 -0.0008951488 0.001588896 0.022044229 0.0401068306
## 6 0.008536849 0.0114997861 0.012952848 -0.019311882 -0.0189161282
## 153 154 155 156 157 158
## 1 0.0023601790 0.011905481 0.0006204743 -0.012942778 0.01404482 0.000920202
## 2 -0.0013594731 0.007696514 -0.0012784462 0.015830158 0.01897627 -0.003502630
## 3 -0.0076637006 0.008063583 -0.0062521988 0.024313211 0.03206522 -0.004643699
## 4 0.0017137954 0.011488425 0.0009613227 -0.001267765 0.01760593 -0.002186207
## 5 -0.0005853487 0.001027533 -0.0044086043 -0.013800808 -0.00497558 0.011981699
## 6 -0.0106367001 0.007604024 -0.0081706015 0.032949575 0.03863542 -0.005710462
## 159 160 161 162 163
## 1 -0.0007949765 0.003193002 0.0045257738 0.009395689 0.0041987494
## 2 0.0287601794 0.003745085 0.0004113984 0.016918872 -0.0008796406
## 3 0.0391602155 -0.000218887 -0.0042597954 0.024654828 -0.0054219707
## 4 0.0102905116 0.002013686 0.0020385656 0.012448195 0.0018631037
## 5 0.0016176024 0.015494919 0.0127287117 0.004937368 0.0084803569
## 6 0.0475303250 -0.002344985 -0.0071587616 0.028831002 -0.0081729117
## 164 165 166 167 168
## 1 -0.00392433234 -0.0023600385 0.001967614 -0.011321777 0.0029496722
## 2 0.00440304478 0.0012644868 -0.003201622 0.025484101 -0.0049949065
## 3 -0.01045240195 0.0024324087 -0.038113423 0.023841313 -0.0051602369
## 4 0.00004242029 0.0003990989 -0.011187447 0.002607471 -0.0003768053
## 5 -0.00030568005 -0.0108704681 0.098466807 -0.001111062 0.0044572241
## 6 -0.01585730768 0.0043724621 -0.058583640 0.027986836 -0.0059378143
## 169 170 171 172 173
## 1 0.015217946 0.004114350 -0.0043403868 0.0083684537 -0.0083944563
## 2 0.001225486 -0.007299012 0.0065921167 0.0033999972 0.0138377613
## 3 -0.001994378 -0.006002992 0.0081005734 -0.0008572257 0.0142479004
## 4 0.007850553 0.001505346 -0.0005794382 0.0044517043 -0.0001749224
## 5 0.027287031 -0.010655817 0.0015200505 0.0235414466 -0.0006747738
## 6 -0.006377870 -0.005908467 0.0105618798 -0.0042845362 0.0176682524
## 174 175 176 177 178
## 1 0.0014428126 0.0026023889 0.0255912444 0.007164711 0.002257197
## 2 -0.0030325344 -0.0051320139 -0.0004020903 -0.003011996 -0.001527886
## 3 -0.0003812714 -0.0011620348 0.0020206981 -0.012118216 -0.008177619
## 4 0.0003986194 0.0003034535 0.0188387008 0.004128233 -0.001755263
## 5 -0.0044453017 -0.0044756973 -0.0065729146 0.002954176 0.023884375
## 6 0.0009549389 0.0003930756 -0.0001394081 -0.017461496 -0.012301073
## 179 180 181 182 183
## 1 0.003096986 0.0019587869 0.0016497562 0.002995060 -0.0019106683
## 2 -0.006070265 -0.0025537798 -0.0039369213 -0.004525993 0.0024566483
## 3 -0.007968142 -0.0031526275 0.0036613254 -0.008543078 -0.0003739094
## 4 -0.001518515 0.0003010011 0.0009028472 -0.001411743 -0.0024421702
## 5 0.011147722 0.0017259077 -0.0118238203 0.015273312 0.0174154351
## 6 -0.009960207 -0.0036145997 0.0074808916 -0.011515406 -0.0013895737
## 184 185 186 187 188
## 1 0.0413463773 0.008425758 0.0059396676 0.0009413058 0.002776341
## 2 0.0002547852 -0.003475617 0.0025810729 -0.0032467494 0.001304545
## 3 0.0203650666 -0.009614040 -0.0105978379 -0.0058567893 -0.006241212
## 4 0.0289179218 0.003551157 0.0060218418 -0.0024194340 0.002845459
## 5 -0.0044214866 0.011061770 0.0009240284 0.0151723331 0.001637358
## 6 0.0240063589 -0.014141597 -0.0169900176 -0.0077154418 -0.009671382
## 189 190 191 192 193
## 1 0.003396460 -0.006309565 -0.0168810548 -0.0031506176 -0.005613716
## 2 -0.006990420 0.010449106 0.0208089449 0.0025393874 0.006740588
## 3 -0.007538612 0.011588280 0.0072875534 0.0071099183 0.004473937
## 4 0.001413568 -0.001088911 -0.0025906084 0.0003374518 -0.003773602
## 5 -0.012003236 0.006532009 -0.0004964028 -0.0122205442 0.020325889
## 6 -0.008107989 0.014382032 0.0062334142 0.0109500749 0.004625278
## 194 195 196 197 198
## 1 -0.006243582 -0.004983401 -0.0029748296 -0.0005210418 0.0016690762
## 2 0.004371289 0.004802158 0.0025351971 -0.0008901503 -0.0039625202
## 3 -0.016719713 -0.009596298 0.0085221950 0.0061603079 -0.0005290231
## 4 -0.001572411 -0.000465783 -0.0006994657 0.0005939671 0.0011241667
## 5 0.002076577 -0.001090615 -0.0043523599 -0.0116189273 -0.0116381374
## 6 -0.024778055 -0.014549982 0.0126790741 0.0103698335 0.0013310605
## 199 200
## 1 0.0367733930 0.002986550
## 2 0.0001706547 -0.005459988
## 3 0.0156739026 -0.002889366
## 4 0.0255731553 0.001134339
## 5 -0.0018951826 -0.008925712
## 6 0.0177614665 -0.001902436#Matriz M
n <- nrow(matriz_x)
matriz_M <- diag(n) - matriz_P
head(matriz_M)## 1 2 3 4 5 6
## 1 0.968185406 -0.0037034602 -0.01758786 -0.022508722 -0.0059178537 -0.01974129
## 2 -0.003703460 0.9753951951 -0.03447285 -0.012120221 0.0004597074 -0.04154714
## 3 -0.017587861 -0.0344728495 0.93233178 -0.026410473 0.0141470892 -0.08506815
## 4 -0.022508722 -0.0121202208 -0.02641047 0.979680185 0.0016776287 -0.03138114
## 5 -0.005917854 0.0004597074 0.01414709 0.001677629 0.9516275359 0.02300480
## 6 -0.019741287 -0.0415471420 -0.08506815 -0.031381139 0.0230047960 0.89194683
## 7 8 9 10 11
## 1 0.003964913 0.0016071128 0.0058291615 -0.001421804 0.002168503
## 2 -0.015101307 -0.0024432890 -0.0063462287 0.003663155 -0.002485740
## 3 -0.012176441 0.0003834528 -0.0220657545 0.003394744 -0.002292606
## 4 -0.003373267 -0.0006504267 -0.0009492958 0.001311471 0.001747623
## 5 -0.001419930 0.0036539819 0.0241326482 -0.007110009 -0.009967185
## 6 -0.013397526 0.0005956252 -0.0324090899 0.003700809 -0.002853121
## 12 13 14 15 16
## 1 -0.0002759271 -0.011079803 0.0018040194 -0.015540826 -0.026214803
## 2 0.0032037695 -0.025864615 -0.0008626337 -0.003574967 -0.008868805
## 3 0.0111934245 -0.042888059 -0.0069060350 -0.004272134 -0.022703414
## 4 -0.0004375016 -0.016265742 -0.0004952366 -0.011268392 -0.022780018
## 5 0.0067191936 -0.008010246 0.0119590637 -0.009198107 0.009839149
## 6 0.0145749642 -0.051950428 -0.0110403269 -0.002643624 -0.026876592
## 17 18 19 20 21
## 1 -0.03915388 -0.028866660 0.0030446199 -0.000749125 -0.016155514
## 2 -0.02564936 0.000720293 -0.0071457201 -0.003240265 -0.002271601
## 3 -0.06550938 -0.006492895 -0.0050758153 0.001537902 -0.001742739
## 4 -0.03416510 -0.019501862 -0.0008189455 -0.001968809 -0.009949161
## 5 -0.01193130 -0.002531157 -0.0011497447 -0.002059947 -0.018716452
## 6 -0.08070465 -0.005662454 -0.0057362342 0.003175472 0.001073962
## 22 23 24 25 26
## 1 -0.0034333941 0.004316663 -0.005388466 0.0028420546 -0.003165795
## 2 0.0054681525 -0.016806251 0.002823854 -0.0047916106 0.005776572
## 3 0.0078040763 -0.014422778 0.007857187 -0.0053003997 0.005590199
## 4 0.0008765953 0.000107821 -0.001795623 0.0001953947 0.000605781
## 5 -0.0101482600 -0.029805892 -0.009631299 -0.0016052193 -0.004805308
## 6 0.0099500685 -0.014983505 0.011271156 -0.0068710163 0.006332393
## 27 28 29 30 31
## 1 0.002681876 -0.005390598 -0.007082428 -0.0010532517 -0.017442057
## 2 -0.005609148 0.003936020 0.002448325 -0.0069889995 0.004638734
## 3 0.002015896 0.008802296 0.009814065 -0.0028884407 0.009107492
## 4 -0.001115757 -0.001728407 -0.003979545 -0.0008445642 -0.008964771
## 5 0.001277872 -0.006801279 -0.004524996 -0.0225484790 -0.013979429
## 6 0.004069901 0.012140107 0.014335892 -0.0010838046 0.014493445
## 32 33 34 35 36
## 1 -0.0026253735 0.00007829225 -0.0015102737 -0.0008416577 -0.0041787942
## 2 -0.0051955492 0.00221677583 0.0060880287 0.0028577552 0.0073185847
## 3 -0.0011305214 0.00644336221 0.0114263483 -0.0065243581 0.0020501923
## 4 -0.0016461471 0.00334836745 -0.0006446965 -0.0009256259 -0.0013001052
## 5 -0.0195427955 -0.02040057341 0.0114424018 0.0137641346 0.0105763886
## 6 0.0009670167 0.00900292961 0.0138701490 -0.0114936966 0.0001144943
## 37 38 39 40 41
## 1 -0.0017327653 -0.01100707 0.001115782 -0.0126410441 -0.0073136600
## 2 0.0053479204 -0.02391753 -0.015069418 -0.0008899392 0.0007424149
## 3 0.0303344305 -0.03786954 -0.015498591 0.0040621941 0.0060140321
## 4 -0.0001262853 -0.01826930 -0.004154417 -0.0093369705 -0.0037685103
## 5 -0.0040538823 0.01140309 -0.008911453 -0.0028637360 -0.0113697277
## 6 0.0425433040 -0.04608851 -0.017539147 0.0079045093 0.0096917200
## 42 43 44 45 46
## 1 -0.009811140 -0.0022075484 -0.0033944730 0.0007196211 -0.004887768
## 2 -0.006867569 0.0072554645 0.0038024488 -0.0180678107 -0.002634461
## 3 -0.006323815 0.0201607339 0.0076354001 -0.0203916189 0.001512283
## 4 -0.009004553 -0.0002723174 0.0005124565 -0.0048484101 -0.003422348
## 5 -0.006311546 0.0053101606 -0.0128093190 -0.0138702814 -0.010782422
## 6 -0.005464233 0.0266180754 0.0104089307 -0.0233681422 0.003912381
## 47 48 49 50 51
## 1 -0.000636477 -0.007218179 -0.0085812388 0.0005966116 -0.002124699
## 2 -0.002101190 0.001158588 0.0007964303 -0.0051694004 0.004348470
## 3 0.003339865 0.014848525 0.0091883803 -0.0005973611 0.011987797
## 4 0.001340547 -0.005349817 -0.0019540716 0.0009760684 0.003289900
## 5 -0.022602305 -0.001695566 -0.0323525873 -0.0221912225 -0.026565676
## 6 0.006217283 0.022098485 0.0153734645 0.0013464757 0.016954994
## 52 53 54 55 56
## 1 0.0016233017 -0.01794311515 -0.027813359 -0.005972562 -0.033101095
## 2 -0.0001020848 -0.00248737108 -0.010730919 0.004358107 -0.008569113
## 3 -0.0056863913 -0.00255547165 -0.028524124 0.014331057 -0.029230585
## 4 -0.0008084888 -0.01382880419 -0.024362404 -0.003022021 -0.027797530
## 5 0.0153479213 0.00001551011 0.009370305 -0.001299242 0.014705638
## 6 -0.0096356490 -0.00051857897 -0.034474036 0.019967656 -0.035690206
## 57 58 59 60 61
## 1 0.005429990 0.0003563637 -0.018405772 -0.0007718026 0.0019216266
## 2 -0.025385846 -0.0025162950 -0.005689590 0.0010323673 -0.0006979854
## 3 -0.030580388 0.0004207625 -0.006926438 0.0117697000 -0.0025139247
## 4 -0.004858263 -0.0010236294 -0.016254362 -0.0011481807 0.0019962776
## 5 -0.009685108 -0.0003442756 0.006457950 0.0018097259 -0.0069605734
## 6 -0.036560576 0.0010324225 -0.005957259 0.0164843646 -0.0039102251
## 62 63 64 65 66
## 1 -0.028730158 -0.006115473 0.00575888212 -0.0054494293 0.0036138722
## 2 -0.001883112 0.004117580 -0.00734651661 -0.0108369324 -0.0024431192
## 3 -0.011445493 0.009526818 0.00086188472 -0.0071867691 -0.0100832760
## 4 -0.020972764 -0.001582491 0.00007101528 -0.0086763845 -0.0007278373
## 5 0.002291898 -0.011313231 0.00316567129 0.0008682326 0.0190600226
## 6 -0.012199763 0.013431892 0.00245372803 -0.0062556242 -0.0156958702
## 67 68 69 70 71
## 1 0.011617705 -0.0005469009 -0.002934147 -0.0103026731 -0.0115071337
## 2 -0.012115501 0.0014442658 0.003175949 -0.0032133517 -0.0025518083
## 3 -0.008597360 0.0020694491 0.012947005 0.0042415718 -0.0000402868
## 4 0.001728730 -0.0007813228 -0.001700562 -0.0091774525 -0.0082015202
## 5 0.009352013 0.0058163138 0.001368084 0.0001750268 -0.0091307843
## 6 -0.010853193 0.0019046559 0.017786805 0.0085259610 0.0025652860
## 72 73 74 75 76
## 1 -0.0023494857 0.0099782744 -0.001333042 -0.002111718 -0.02743539
## 2 -0.0015927828 -0.0205623129 0.001862759 0.001329879 -0.03622436
## 3 0.0027003456 -0.0179995065 0.006913584 0.008431787 -0.08080567
## 4 -0.0005687564 -0.0015483245 0.002118511 -0.001664044 -0.03321476
## 5 -0.0155235094 0.0004663288 -0.020097952 0.001078586 0.01269759
## 6 0.0050745314 -0.0209680704 0.010028399 0.011716008 -0.10212156
## 77 78 79 80 81
## 1 0.003463964 0.0029172672 0.017683650 -0.0007147327 0.002945595
## 2 -0.002686720 -0.0067346299 -0.024228182 0.0008202598 -0.010766108
## 3 -0.005726683 -0.0002880732 -0.021708315 0.0021312910 -0.007858672
## 4 0.002190870 -0.0012727699 0.001853458 0.0007675508 -0.002180415
## 5 -0.005719769 0.0008449312 0.004702395 -0.0084909965 -0.002685843
## 6 -0.008191585 0.0010789394 -0.026445857 0.0028254636 -0.008427233
## 82 83 84 85 86
## 1 -0.003301367 -0.0003371442 -0.003008872 -0.0133864079 -0.012804381
## 2 0.005259489 -0.0080091104 -0.021214491 -0.0044826317 -0.001434141
## 3 0.014361239 -0.0056872082 -0.025430724 -0.0018014995 0.006450985
## 4 0.003106977 -0.0020745524 -0.011083875 -0.0116644922 -0.004448956
## 5 -0.029263537 -0.0120916478 0.004004360 0.0007270034 -0.042272137
## 6 0.020398275 -0.0053531520 -0.029761661 0.0005762994 0.013222963
## 87 88 89 90 91 92
## 1 0.0050107774 -0.021325247 -0.01477712 -0.01730354 -0.0015829227 0.003428544
## 2 -0.0104062858 -0.016871282 -0.01195406 -0.01962937 0.0037024430 -0.002271494
## 3 -0.0060499645 -0.034864659 -0.01553121 -0.03596225 -0.0017972966 0.002274857
## 4 -0.0011010411 -0.021109728 -0.01078879 -0.02078517 -0.0007708485 0.004445140
## 5 0.0005368574 0.001216796 -0.03209347 0.01083455 0.0096213148 -0.024396046
## 6 -0.0063546389 -0.042225687 -0.01531560 -0.04384692 -0.0045820694 0.004157674
## 93 94 95 96 97
## 1 -0.021743646 -0.032844286 0.0017969091 -0.015241189 -0.002952671
## 2 -0.004504497 -0.002810524 -0.0018859775 -0.007258299 0.005717905
## 3 -0.010332240 -0.016334217 -0.0025491337 -0.010699649 -0.001945193
## 4 -0.015370593 -0.022465802 -0.0003619854 -0.011921848 -0.001502198
## 5 -0.011815717 -0.009089004 0.0056512310 -0.012502683 0.014719072
## 6 -0.010129518 -0.017938274 -0.0040199493 -0.010650219 -0.005524197
## 98 99 100 101 102
## 1 -0.0035767892 -0.028356283 -0.013863910 -0.002413055 -0.048451432
## 2 0.0002569184 0.001103946 -0.013492546 0.003463899 -0.002505832
## 3 0.0051082293 -0.005033977 -0.021019326 0.018700619 -0.028158653
## 4 -0.0021930049 -0.019541145 -0.015158105 0.005084294 -0.032017325
## 5 -0.0048131207 0.001059394 0.001727939 -0.047004605 -0.013885205
## 6 0.0076941858 -0.003885221 -0.024316278 0.027995795 -0.032782646
## 103 104 105 106 107
## 1 -0.0053168995 -0.002653151 -0.00009995288 -0.02526116 0.004749254
## 2 0.0064891634 0.001622762 0.00260929368 -0.01473435 -0.009061668
## 3 0.0097834932 0.005171523 0.01872241182 -0.03424913 -0.007999778
## 4 -0.0005771213 -0.001310801 -0.00023665627 -0.02418343 0.001454019
## 5 -0.0066758788 -0.001925084 0.00094993885 0.01024973 -0.014135529
## 6 0.0126359821 0.007031004 0.02604391369 -0.04185212 -0.009071375
## 108 109 110 111 112
## 1 0.0007485001 0.005672610 -0.0026188337 -0.005771231 -0.0086629510
## 2 0.0015631086 -0.005067056 0.0057525446 0.003484357 0.0003918361
## 3 0.0010986470 -0.006187925 0.0168470426 0.019432650 0.0100643251
## 4 0.0024500010 0.003708917 -0.0008908024 0.003153845 -0.0063886779
## 5 -0.0102863033 -0.013195848 0.0040703359 -0.050498338 -0.0021044217
## 6 0.0008856774 -0.008045006 0.0224155724 0.029724867 0.0155977870
## 113 114 115 116 117
## 1 0.0001175903 -0.001545444 -0.003597274 -0.009832110 -0.0011860601
## 2 0.0026527589 0.002098966 -0.020824272 -0.017995010 -0.0016157498
## 3 0.0027944289 0.007044843 -0.024296887 -0.027038525 0.0013020365
## 4 -0.0007764986 -0.001167366 -0.011561255 -0.012900823 -0.0005203164
## 5 0.0129649799 0.003551416 0.005278239 -0.006482524 -0.0093448438
## 6 0.0021378444 0.009213841 -0.028199734 -0.031807687 0.0026011247
## 118 119 120 121 122
## 1 -0.0005756822 -0.027543034 0.007546088 -0.010092883 0.001256304
## 2 0.0028243277 -0.015850759 -0.013278881 -0.005764217 -0.018516539
## 3 -0.0023639602 -0.037358217 -0.014491705 -0.004755727 -0.019680129
## 4 0.0005306074 -0.023694853 0.000524932 -0.007492325 -0.003474396
## 5 0.0026096379 -0.007535961 -0.004285915 -0.015780813 -0.022947464
## 6 -0.0049680355 -0.044936677 -0.017897096 -0.003138228 -0.021878187
## 123 124 125 126 127
## 1 -0.0030494045 0.0045758255 -0.028066830 0.0005171007 -0.001157018
## 2 0.0059078442 -0.0087758902 -0.004441707 -0.0029373475 -0.032144210
## 3 0.0030689587 0.0010304012 -0.014097201 -0.0008912172 -0.047216834
## 4 0.0001193038 -0.0010866591 -0.018687216 0.0003336806 -0.013069487
## 5 0.0008682083 0.0006374068 -0.018442316 -0.0102855100 0.000672922
## 6 0.0023381941 0.0035058869 -0.014427641 -0.0003635419 -0.057912269
## 128 129 130 131 132
## 1 -0.0004007523 0.0030631966 -0.00009101935 0.027495731 -0.003753654
## 2 0.0023952609 0.0008164906 -0.00572752482 -0.037678848 0.006663725
## 3 -0.0070207827 0.0300466960 0.00046601269 -0.032569001 0.019849158
## 4 -0.0004954016 0.0015646169 0.00108166432 0.003453268 0.004475979
## 5 0.0115576380 -0.0067207540 -0.02884527971 0.003180179 -0.039230507
## 6 -0.0120335412 0.0431300359 0.00348480049 -0.038958460 0.028413252
## 133 134 135 136 137 138
## 1 0.018387688 -0.016054268 -0.014553526 0.016977864 0.015872880 -0.022599957
## 2 -0.021052314 -0.002787004 -0.025500235 -0.023507277 -0.022276334 0.001616463
## 3 -0.018150282 -0.003146075 -0.045757412 -0.008206339 -0.012739833 0.001349017
## 4 0.003028304 -0.011444971 -0.019286583 0.001706439 0.001384722 -0.012684888
## 5 0.008904895 -0.008395455 -0.001440959 -0.001213916 0.001496246 -0.020292857
## 6 -0.022657489 -0.001230203 -0.056018846 -0.006547489 -0.013584550 0.005262522
## 139 140 141 142 143
## 1 0.006392195 0.006815004 0.003521477 -0.029619162 -0.013667000
## 2 -0.014262012 -0.003298025 -0.005167978 -0.007993406 -0.000924610
## 3 -0.012549005 0.021062955 -0.004700184 -0.023291407 0.001923799
## 4 -0.001251770 0.002415945 -0.000221457 -0.021841085 -0.009390502
## 5 -0.001398814 -0.003536289 0.003431624 -0.011424455 -0.006978404
## 6 -0.014626764 0.030731387 -0.006162335 -0.026670719 0.005104696
## 144 145 146 147 148
## 1 -0.0005481730 -0.0019927013 -0.001662813 -0.003293329 -0.025005933
## 2 0.0005880946 -0.0042853267 0.003996589 0.005943807 -0.003038181
## 3 0.0067065339 0.0006231371 -0.003672735 0.002606658 -0.008685493
## 4 0.0026509430 -0.0005364973 -0.000774948 -0.001167379 -0.019804986
## 5 -0.0241251723 -0.0220725196 0.011027079 0.009327458 0.007948305
## 6 0.0102282337 0.0032134578 -0.007485127 0.001343292 -0.008536849
## 149 150 151 152 153
## 1 0.0131117591 0.005633951 -0.008303315 -0.0028578847 -0.0023601790
## 2 -0.0207572750 -0.013247648 0.005440820 0.0002684596 0.0013594731
## 3 -0.0112517037 -0.011242578 0.013335024 0.0118643771 0.0076637006
## 4 0.0001254037 -0.001372099 -0.001275566 0.0027561870 -0.0017137954
## 5 0.0008951488 -0.001588896 -0.022044229 -0.0401068306 0.0005853487
## 6 -0.0114997861 -0.012952848 0.019311882 0.0189161282 0.0106367001
## 154 155 156 157 158
## 1 -0.011905481 -0.0006204743 0.012942778 -0.01404482 -0.000920202
## 2 -0.007696514 0.0012784462 -0.015830158 -0.01897627 0.003502630
## 3 -0.008063583 0.0062521988 -0.024313211 -0.03206522 0.004643699
## 4 -0.011488425 -0.0009613227 0.001267765 -0.01760593 0.002186207
## 5 -0.001027533 0.0044086043 0.013800808 0.00497558 -0.011981699
## 6 -0.007604024 0.0081706015 -0.032949575 -0.03863542 0.005710462
## 159 160 161 162 163
## 1 0.0007949765 -0.003193002 -0.0045257738 -0.009395689 -0.0041987494
## 2 -0.0287601794 -0.003745085 -0.0004113984 -0.016918872 0.0008796406
## 3 -0.0391602155 0.000218887 0.0042597954 -0.024654828 0.0054219707
## 4 -0.0102905116 -0.002013686 -0.0020385656 -0.012448195 -0.0018631037
## 5 -0.0016176024 -0.015494919 -0.0127287117 -0.004937368 -0.0084803569
## 6 -0.0475303250 0.002344985 0.0071587616 -0.028831002 0.0081729117
## 164 165 166 167 168
## 1 0.00392433234 0.0023600385 -0.001967614 0.011321777 -0.0029496722
## 2 -0.00440304478 -0.0012644868 0.003201622 -0.025484101 0.0049949065
## 3 0.01045240195 -0.0024324087 0.038113423 -0.023841313 0.0051602369
## 4 -0.00004242029 -0.0003990989 0.011187447 -0.002607471 0.0003768053
## 5 0.00030568005 0.0108704681 -0.098466807 0.001111062 -0.0044572241
## 6 0.01585730768 -0.0043724621 0.058583640 -0.027986836 0.0059378143
## 169 170 171 172 173
## 1 -0.015217946 -0.004114350 0.0043403868 -0.0083684537 0.0083944563
## 2 -0.001225486 0.007299012 -0.0065921167 -0.0033999972 -0.0138377613
## 3 0.001994378 0.006002992 -0.0081005734 0.0008572257 -0.0142479004
## 4 -0.007850553 -0.001505346 0.0005794382 -0.0044517043 0.0001749224
## 5 -0.027287031 0.010655817 -0.0015200505 -0.0235414466 0.0006747738
## 6 0.006377870 0.005908467 -0.0105618798 0.0042845362 -0.0176682524
## 174 175 176 177 178
## 1 -0.0014428126 -0.0026023889 -0.0255912444 -0.007164711 -0.002257197
## 2 0.0030325344 0.0051320139 0.0004020903 0.003011996 0.001527886
## 3 0.0003812714 0.0011620348 -0.0020206981 0.012118216 0.008177619
## 4 -0.0003986194 -0.0003034535 -0.0188387008 -0.004128233 0.001755263
## 5 0.0044453017 0.0044756973 0.0065729146 -0.002954176 -0.023884375
## 6 -0.0009549389 -0.0003930756 0.0001394081 0.017461496 0.012301073
## 179 180 181 182 183
## 1 -0.003096986 -0.0019587869 -0.0016497562 -0.002995060 0.0019106683
## 2 0.006070265 0.0025537798 0.0039369213 0.004525993 -0.0024566483
## 3 0.007968142 0.0031526275 -0.0036613254 0.008543078 0.0003739094
## 4 0.001518515 -0.0003010011 -0.0009028472 0.001411743 0.0024421702
## 5 -0.011147722 -0.0017259077 0.0118238203 -0.015273312 -0.0174154351
## 6 0.009960207 0.0036145997 -0.0074808916 0.011515406 0.0013895737
## 184 185 186 187 188
## 1 -0.0413463773 -0.008425758 -0.0059396676 -0.0009413058 -0.002776341
## 2 -0.0002547852 0.003475617 -0.0025810729 0.0032467494 -0.001304545
## 3 -0.0203650666 0.009614040 0.0105978379 0.0058567893 0.006241212
## 4 -0.0289179218 -0.003551157 -0.0060218418 0.0024194340 -0.002845459
## 5 0.0044214866 -0.011061770 -0.0009240284 -0.0151723331 -0.001637358
## 6 -0.0240063589 0.014141597 0.0169900176 0.0077154418 0.009671382
## 189 190 191 192 193
## 1 -0.003396460 0.006309565 0.0168810548 0.0031506176 0.005613716
## 2 0.006990420 -0.010449106 -0.0208089449 -0.0025393874 -0.006740588
## 3 0.007538612 -0.011588280 -0.0072875534 -0.0071099183 -0.004473937
## 4 -0.001413568 0.001088911 0.0025906084 -0.0003374518 0.003773602
## 5 0.012003236 -0.006532009 0.0004964028 0.0122205442 -0.020325889
## 6 0.008107989 -0.014382032 -0.0062334142 -0.0109500749 -0.004625278
## 194 195 196 197 198
## 1 0.006243582 0.004983401 0.0029748296 0.0005210418 -0.0016690762
## 2 -0.004371289 -0.004802158 -0.0025351971 0.0008901503 0.0039625202
## 3 0.016719713 0.009596298 -0.0085221950 -0.0061603079 0.0005290231
## 4 0.001572411 0.000465783 0.0006994657 -0.0005939671 -0.0011241667
## 5 -0.002076577 0.001090615 0.0043523599 0.0116189273 0.0116381374
## 6 0.024778055 0.014549982 -0.0126790741 -0.0103698335 -0.0013310605
## 199 200
## 1 -0.0367733930 -0.002986550
## 2 -0.0001706547 0.005459988
## 3 -0.0156739026 0.002889366
## 4 -0.0255731553 -0.001134339
## 5 0.0018951826 0.008925712
## 6 -0.0177614665 0.001902436Compruebe que los residuos en el objeto “modelo_ventas” son iguales al producto de M y, donde “y” es la variable endógena en el modelo (“ventas”)
options(scipen = 99999999)
library(magrittr)
residuos_modelo_ventas <- modelo_ventas$residuals
datos_modelo <- modelo_ventas$model
residuos_matrices <- matriz_M %*% datos_modelo$ventas
cbind(
residuos_matrices,
residuos_modelo_ventas,
residuos_modelo_ventas - residuos_matrices
) %>% round(digits = 2) %>% as.data.frame() -> comparacion
names(comparacion) <- c("por_matrices", "En_modelo", "Diferencia")
comparacion## por_matrices En_modelo Diferencia
## 1 -15.93 -15.93 0
## 2 19.33 19.33 0
## 3 38.02 38.02 0
## 4 -15.43 -15.43 0
## 5 5.16 5.16 0
## 6 80.22 80.22 0
## 7 -16.35 -16.35 0
## 8 -22.89 -22.89 0
## 9 -34.40 -34.40 0
## 10 46.09 46.09 0
## 11 -40.56 -40.56 0
## 12 9.25 9.25 0
## 13 5.82 5.82 0
## 14 -19.64 -19.64 0
## 15 -2.74 -2.74 0
## 16 -20.58 -20.58 0
## 17 -4.89 -4.89 0
## 18 -0.83 -0.83 0
## 19 -36.61 -36.61 0
## 20 -8.11 -8.11 0
## 21 11.00 11.00 0
## 22 56.50 56.50 0
## 23 -7.55 -7.55 0
## 24 31.71 31.71 0
## 25 -40.48 -40.48 0
## 26 86.80 86.80 0
## 27 -1.44 -1.44 0
## 28 35.92 35.92 0
## 29 24.51 24.51 0
## 30 -38.94 -38.94 0
## 31 25.44 25.44 0
## 32 -17.24 -17.24 0
## 33 -44.11 -44.11 0
## 34 47.62 47.62 0
## 35 -38.06 -38.06 0
## 36 104.56 104.56 0
## 37 -22.01 -22.01 0
## 38 6.26 6.26 0
## 39 -20.85 -20.85 0
## 40 -8.14 -8.14 0
## 41 3.52 3.52 0
## 42 7.13 7.13 0
## 43 39.33 39.33 0
## 44 29.22 29.22 0
## 45 -13.40 -13.40 0
## 46 8.21 8.21 0
## 47 -42.24 -42.24 0
## 48 -15.16 -15.16 0
## 49 36.15 36.15 0
## 50 -42.33 -42.33 0
## 51 29.60 29.60 0
## 52 -27.94 -27.94 0
## 53 -25.78 -25.78 0
## 54 -16.15 -16.15 0
## 55 20.52 20.52 0
## 56 -34.10 -34.10 0
## 57 32.84 32.84 0
## 58 -8.84 -8.84 0
## 59 -25.90 -25.90 0
## 60 4.38 4.38 0
## 61 -56.13 -56.13 0
## 62 -5.97 -5.97 0
## 63 34.06 34.06 0
## 64 -22.00 -22.00 0
## 65 -22.92 -22.92 0
## 66 -33.91 -33.91 0
## 67 -25.98 -25.98 0
## 68 -24.10 -24.10 0
## 69 15.18 15.18 0
## 70 -12.96 -12.96 0
## 71 -2.78 -2.78 0
## 72 -39.34 -39.34 0
## 73 9.10 9.10 0
## 74 -23.58 -23.58 0
## 75 16.53 16.53 0
## 76 41.92 41.92 0
## 77 -61.13 -61.13 0
## 78 -11.80 -11.80 0
## 79 42.30 42.30 0
## 80 -28.28 -28.28 0
## 81 -18.10 -18.10 0
## 82 55.90 55.90 0
## 83 -32.84 -32.84 0
## 84 1.99 1.99 0
## 85 -7.85 -7.85 0
## 86 2.06 2.06 0
## 87 -18.80 -18.80 0
## 88 -12.42 -12.42 0
## 89 -34.44 -34.44 0
## 90 -0.71 -0.71 0
## 91 -19.86 -19.86 0
## 92 -71.04 -71.04 0
## 93 5.47 5.47 0
## 94 -1.83 -1.83 0
## 95 -22.68 -22.68 0
## 96 -9.60 -9.60 0
## 97 30.46 30.46 0
## 98 2.80 2.80 0
## 99 -1.39 -1.39 0
## 100 -6.92 -6.92 0
## 101 47.13 47.13 0
## 102 13.67 13.67 0
## 103 74.24 74.24 0
## 104 8.29 8.29 0
## 105 5.20 5.20 0
## 106 -23.16 -23.16 0
## 107 -39.16 -39.16 0
## 108 -36.55 -36.55 0
## 109 -51.39 -51.39 0
## 110 14.93 14.93 0
## 111 31.77 31.77 0
## 112 0.85 0.85 0
## 113 3.55 3.55 0
## 114 20.05 20.05 0
## 115 1.25 1.25 0
## 116 -6.04 -6.04 0
## 117 -5.24 -5.24 0
## 118 -59.49 -59.49 0
## 119 -9.08 -9.08 0
## 120 -15.33 -15.33 0
## 121 -22.74 -22.74 0
## 122 -6.98 -6.98 0
## 123 52.60 52.60 0
## 124 -7.38 -7.38 0
## 125 6.99 6.99 0
## 126 -36.29 -36.29 0
## 127 51.55 51.55 0
## 128 -45.71 -45.71 0
## 129 -38.99 -38.99 0
## 130 -49.74 -49.74 0
## 131 137.77 137.77 0
## 132 68.15 68.15 0
## 133 29.49 29.49 0
## 134 4.04 4.04 0
## 135 2.44 2.44 0
## 136 24.96 24.96 0
## 137 14.83 14.83 0
## 138 18.65 18.65 0
## 139 -13.45 -13.45 0
## 140 -17.13 -17.13 0
## 141 -36.00 -36.00 0
## 142 -7.79 -7.79 0
## 143 -5.46 -5.46 0
## 144 -38.02 -38.02 0
## 145 -33.90 -33.90 0
## 146 -7.02 -7.02 0
## 147 57.02 57.02 0
## 148 -24.42 -24.42 0
## 149 5.76 5.76 0
## 150 -21.33 -21.33 0
## 151 60.96 60.96 0
## 152 -37.40 -37.40 0
## 153 3.70 3.70 0
## 154 -11.53 -11.53 0
## 155 5.57 5.57 0
## 156 20.34 20.34 0
## 157 -6.39 -6.39 0
## 158 0.10 0.10 0
## 159 35.21 35.21 0
## 160 -12.86 -12.86 0
## 161 -0.28 -0.28 0
## 162 -5.49 -5.49 0
## 163 7.07 7.07 0
## 164 -11.48 -11.48 0
## 165 -17.07 -17.07 0
## 166 43.48 43.48 0
## 167 30.49 30.49 0
## 168 32.76 32.76 0
## 169 9.33 9.33 0
## 170 79.25 79.25 0
## 171 -32.15 -32.15 0
## 172 -2.32 -2.32 0
## 173 -19.07 -19.07 0
## 174 11.45 11.45 0
## 175 56.81 56.81 0
## 176 -20.90 -20.90 0
## 177 10.72 10.72 0
## 178 10.72 10.72 0
## 179 99.16 99.16 0
## 180 0.68 0.68 0
## 181 8.07 8.07 0
## 182 43.24 43.24 0
## 183 -53.93 -53.93 0
## 184 -14.41 -14.41 0
## 185 33.06 33.06 0
## 186 -26.80 -26.80 0
## 187 -11.78 -11.78 0
## 188 2.02 2.02 0
## 189 75.55 75.55 0
## 190 -31.29 -31.29 0
## 191 11.46 11.46 0
## 192 -34.64 -34.64 0
## 193 -47.21 -47.21 0
## 194 -20.94 -20.94 0
## 195 -16.29 -16.29 0
## 196 -54.55 -54.55 0
## 197 -31.98 -31.98 0
## 198 8.34 8.34 0
## 199 -9.58 -9.58 0
## 200 49.59 49.59 0Muestre que los autovalores de x’x son positivos (use el comando eigen)
options(scipen = 99999999)
eigen(x = matriz_xx,symmetric = TRUE)->descomposicion
auto_valores<-descomposicion$values
print(auto_valores)## [1] 311421698.6388 70252.5341 40973.4590 3714.3627 12.7735print(auto_valores>0)## [1] TRUE TRUE TRUE TRUE TRUE···Ejercicio 2··· Carga de datos
load("C:/Users/Keiry/Documents/Eco22/datos_cajas.RData")Estime el modelo propuesto, y colóquele el nombre de “modelo_cajas”
options(scipen = 999999)
modelo_cajas<-lm(formula = Tiempo ~ Distancia+N_cajas,data = datos_cajas)
summary(modelo_cajas)##
## Call:
## lm(formula = Tiempo ~ Distancia + N_cajas, data = datos_cajas)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9.2716 -0.5405 0.5212 1.4051 2.9381
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.3112 5.8573 0.395 0.70007
## Distancia 0.4559 0.1468 3.107 0.00908 **
## N_cajas 0.8772 0.1530 5.732 0.0000943 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.141 on 12 degrees of freedom
## Multiple R-squared: 0.7368, Adjusted R-squared: 0.6929
## F-statistic: 16.8 on 2 and 12 DF, p-value: 0.0003325Calcule las matrices A, P, M
options(scipen = 99999999)
matriz_x_1 <- model.matrix(modelo_cajas)
matriz_xx_1 <- t(matriz_x_1) %*% matriz_x_1
#Matriz A
matriz_A_1 <- solve(matriz_xx_1) %*% t(matriz_x_1)
head(matriz_A_1)## 1 2 3 4 5
## (Intercept) 0.459747079 0.505626389 -0.317731768 0.707001469 0.053149816
## Distancia -0.003015297 -0.009318829 0.018819615 -0.019989342 -0.006641453
## N_cajas -0.017147338 -0.009890695 -0.007919488 -0.004479623 0.011082085
## 6 7 8 9 10
## (Intercept) -0.166576988 0.633594572 -0.125532551 0.1260628274 -0.90735239
## Distancia 0.006550474 -0.009903692 0.009409808 0.0003379213 0.02334256
## N_cajas 0.002768355 -0.016090251 -0.003959744 -0.0038254420 0.01780152
## 11 12 13 14 15
## (Intercept) 0.277217608 0.368482344 0.487274665 -0.3674581822 -0.73350489
## Distancia -0.011931220 -0.007473259 -0.006797416 0.0001559637 0.01645417
## N_cajas 0.006862401 -0.005142468 -0.012793352 0.0238754370 0.01885861#Matriz P
matriz_P_1<- matriz_x_1 %*% matriz_A_1
head(matriz_P_1)## 1 2 3 4 5 6
## 1 0.19781478 0.12715457 0.16766180 0.062524965 -0.03527291 0.057620774
## 2 0.12715457 0.12429524 0.03396629 0.140073563 0.05334477 0.038710181
## 3 0.16766180 0.03396629 0.35585795 -0.137368460 -0.10168744 0.123125512
## 4 0.06252497 0.14007356 -0.13736846 0.257600846 0.15524536 0.006698639
## 5 -0.03527291 0.05334477 -0.10168744 0.155245361 0.18408997 0.046742309
## 6 0.05762077 0.03871018 0.12312551 0.006698639 0.04674231 0.086318088
## 7 8 9 10 11 12
## 1 0.17558129 0.11716423 0.09794605 -0.02906036 -0.01209498 0.09285990
## 2 0.14464850 0.05031648 0.07712923 -0.05676557 0.08187312 0.10451385
## 3 0.07654437 0.21126231 0.10132526 0.20436525 -0.13140718 0.01812731
## 4 0.13352309 -0.03535090 0.05563657 -0.13115591 0.19970367 0.13111432
## 5 0.01345706 -0.01751039 0.03786105 0.05122193 0.18629079 0.07550894
## 6 0.03695559 0.09489609 0.06768043 0.13669435 0.03087301 0.04424689
## 13 14 15
## 1 0.15541865 -0.124024902 -0.05129385
## 2 0.12543897 -0.005427535 -0.03927165
## 3 0.08744449 -0.122465266 0.11324781
## 4 0.10905412 0.112857904 -0.06015778
## 5 0.01789770 0.232858944 0.09995191
## 6 0.04627442 0.067134558 0.11602917#Matriz M
n <- nrow(matriz_x_1)
matriz_M_1 <- diag(n) - matriz_P_1
head(matriz_M_1)## 1 2 3 4 5 6
## 1 0.80218522 -0.12715457 -0.16766180 -0.062524965 0.03527291 -0.057620774
## 2 -0.12715457 0.87570476 -0.03396629 -0.140073563 -0.05334477 -0.038710181
## 3 -0.16766180 -0.03396629 0.64414205 0.137368460 0.10168744 -0.123125512
## 4 -0.06252497 -0.14007356 0.13736846 0.742399154 -0.15524536 -0.006698639
## 5 0.03527291 -0.05334477 0.10168744 -0.155245361 0.81591003 -0.046742309
## 6 -0.05762077 -0.03871018 -0.12312551 -0.006698639 -0.04674231 0.913681912
## 7 8 9 10 11 12
## 1 -0.17558129 -0.11716423 -0.09794605 0.02906036 0.01209498 -0.09285990
## 2 -0.14464850 -0.05031648 -0.07712923 0.05676557 -0.08187312 -0.10451385
## 3 -0.07654437 -0.21126231 -0.10132526 -0.20436525 0.13140718 -0.01812731
## 4 -0.13352309 0.03535090 -0.05563657 0.13115591 -0.19970367 -0.13111432
## 5 -0.01345706 0.01751039 -0.03786105 -0.05122193 -0.18629079 -0.07550894
## 6 -0.03695559 -0.09489609 -0.06768043 -0.13669435 -0.03087301 -0.04424689
## 13 14 15
## 1 -0.15541865 0.124024902 0.05129385
## 2 -0.12543897 0.005427535 0.03927165
## 3 -0.08744449 0.122465266 -0.11324781
## 4 -0.10905412 -0.112857904 0.06015778
## 5 -0.01789770 -0.232858944 -0.09995191
## 6 -0.04627442 -0.067134558 -0.116029172. Compruebe que los residuos en el objeto “modelo_ventas” son iguales al producto de M y, donde “y” es la variable endógena en el modelo (“Tiempo”)
options(scipen = 99999999)
library(magrittr)
residuos_modelo_1<-modelo_cajas$residuals
matriz_y<-datos_cajas$Tiempo
residuos_por_matrices_1<-matriz_M_1%*%matriz_y
comparativa_1<-cbind(residuos_modelo_1,
residuos_por_matrices_1,
residuos_modelo_1-residuos_por_matrices_1) %>% as.data.frame() %>% round(digits = 2)
names(comparativa_1)<-c("residuos_modelo","Residuos_matrices","diferencia")
print(comparativa_1)## residuos_modelo Residuos_matrices diferencia
## 1 -0.76 -0.76 0
## 2 0.13 0.13 0
## 3 -0.32 -0.32 0
## 4 2.94 2.94 0
## 5 -9.27 -9.27 0
## 6 0.77 0.77 0
## 7 1.31 1.31 0
## 8 -2.09 -2.09 0
## 9 1.43 1.43 0
## 10 0.52 0.52 0
## 11 0.52 0.52 0
## 12 1.38 1.38 0
## 13 -1.02 -1.02 0
## 14 2.89 2.89 0
## 15 1.59 1.59 0Muestre que los autovalores de x’x son positivos (use el comando eigen)
descomposicion_1<-eigen(matriz_xx_1)
autovalores_1<-descomposicion_1$values
print(autovalores_1)## [1] 16976.7781334 709.9345923 0.2872743print(autovalores_1>0)## [1] TRUE TRUE TRUE···Ejercicio 3··· Carga de datos
load("C:/Users/Keiry/Documents/Eco22/modelo_estimado.RData")Calcule las matrices A, P, M
options(scipen = 99999999)
matriz_x_2 <- model.matrix(modelo_estimado_1)
matriz_xx_2 <- t(matriz_x_2) %*% matriz_x_2
#Matriz A
matriz_A_2 <- solve(matriz_xx_2) %*% t(matriz_x_2)
head(matriz_A_2)## 1 2 3 4 5
## (Intercept) -0.12023796 0.007496216 0.043732382 -0.019624196 -0.042393783
## poverty -0.01182361 0.003994776 0.008825494 0.000303668 0.003470064
## single 0.02723384 -0.003960021 -0.013241432 0.003081729 0.001105700
## 6 7 8 9 10
## (Intercept) -0.013384345 0.086168745 0.020563005 0.051126534 -0.061552737
## poverty -0.007184049 -0.005862340 -0.005645941 0.005991789 -0.003735449
## single 0.011957829 0.001503614 0.007023918 -0.010326666 0.011869128
## 11 12 13 14 15
## (Intercept) 0.135718387 0.138007251 0.110339408 0.011807385 0.04768336913
## poverty -0.004929205 -0.001636594 0.001368417 -0.001178554 -0.00195483396
## single -0.004046260 -0.008393766 -0.009734111 0.002172555 -0.00001782648
## 16 17 18 19 20
## (Intercept) 0.0907464740 0.048176786 -0.169254531 0.044486937 -0.008259184
## poverty 0.0007228831 0.009531438 0.010760361 -0.004158321 -0.007294945
## single -0.0071913968 -0.014522641 0.003128543 0.003038604 0.011644914
## 21 22 23 24 25
## (Intercept) 0.059181614 -0.063708321 0.092448252 0.038360537 -0.157529384
## poverty -0.003674172 -0.001148784 -0.001319221 0.003193256 0.008768744
## single 0.001131571 0.008802840 -0.004770642 -0.005676113 0.004600706
## 26 27 28 29 30
## (Intercept) 0.044620170 0.0304927049 0.166375633 0.118414317 0.128664592
## poverty 0.001720954 0.0005561012 0.000556971 -0.002282127 -0.002503922
## single -0.004375184 -0.0016612271 -0.013660295 -0.005851051 -0.006476873
## 31 32 33 34 35
## (Intercept) 0.107937093 -0.1051632730 -0.027965571 -0.0501481154 0.017386353
## poverty -0.001788055 0.0002829526 -0.007804338 0.0006967702 -0.001834012
## single -0.005547989 0.0106606021 0.014026244 0.0052819644 0.002505176
## 36 37 38 39 40
## (Intercept) 0.024252854 0.023645985 0.105327700 0.048817888 -0.0331645748
## poverty 0.008043818 -0.003306313 0.001343172 -0.003316237 0.0044735326
## single -0.010537327 0.003806104 -0.009259812 0.001596010 -0.0009725754
## 41 42 43 44 45
## (Intercept) 0.113989696 0.019694998 -0.007198508 0.088571062 0.0750108562
## poverty 0.003027344 0.007474015 0.003510625 -0.002705869 -0.0045514234
## single -0.012145012 -0.009417501 -0.002052983 -0.002682507 0.0008383681
## 46 47 48 49 50
## (Intercept) 0.040382842 0.003712695 0.0668225421 0.10491355 0.0464353985
## poverty -0.005272687 -0.003543426 -0.0007647365 0.01391857 -0.0004572901
## single 0.004803970 0.005864667 -0.0032060825 -0.02505570 -0.0017930470
## 51
## (Intercept) -0.5219277203
## poverty -0.0008592616
## single 0.0488974529#Matriz P
matriz_P_2<- matriz_x_2 %*% matriz_A_2
head(matriz_P_2)## 1 2 3 4 5 6
## 1 0.161611077 -0.0127796253 -0.06530809 0.02720791 0.004995312 0.0922377599
## 2 -0.012779625 0.0314650769 0.04501952 0.02109951 0.030700881 -0.0008717607
## 3 -0.065308090 0.0450195150 0.07855895 0.01942366 0.038838489 -0.0291165550
## 4 0.027207907 0.0210995096 0.01942366 0.02234121 0.024424173 0.0206710383
## 5 0.004995312 0.0307008811 0.03883849 0.02442417 0.034582636 0.0053388207
## 6 0.092237760 -0.0008717607 -0.02911656 0.02067104 0.005338821 0.0601833060
## 7 8 9 10 11 12
## 1 0.054323132 0.069626967 -0.04201951 0.074183205 0.033001099 0.003083400
## 2 0.001455597 0.003098691 0.03662700 0.009945418 0.003418230 0.013002220
## 3 -0.014989380 -0.017199893 0.06046699 -0.009262056 -0.006160696 0.015462090
## 4 0.014082445 0.018604926 0.01844742 0.024537798 0.010848882 0.011239145
## 5 -0.001730668 0.005605850 0.03109378 0.018826182 -0.004571400 0.003299178
## 6 0.046325314 0.049657601 -0.01450742 0.045082769 0.037959510 0.020240409
## 13 14 15 16 17 18
## 1 -0.016405789 0.03215008 0.029639461 -0.005512265 -0.07276090 -0.02659707
## 2 0.022207584 0.01628493 0.013464255 0.020623577 0.04701342 0.05395399
## 3 0.033552760 0.01148264 0.008395947 0.028256192 0.08341328 0.07942810
## 4 0.013630280 0.01994557 0.017363227 0.014862970 0.01923696 0.03431040
## 5 0.013568208 0.01751464 0.011882559 0.014010488 0.04011594 0.06569084
## 6 0.006103986 0.02642762 0.028114813 0.010887113 -0.03318595 -0.02487159
## 19 20 21 22 23 24
## 1 0.050098243 0.091879085 0.041928113 0.051718351 0.012223150 -0.013749255
## 2 0.007076090 -0.001274712 0.008264093 0.017535492 0.014631413 0.028647885
## 3 -0.006166430 -0.029557504 -0.002194011 0.007506379 0.015017951 0.041491243
## 4 0.017215896 0.020302131 0.016291379 0.025114767 0.014407468 0.018855703
## 5 0.006788032 0.004534238 0.006456323 0.025419303 0.008805392 0.025526380
## 6 0.040086662 0.060424327 0.036499323 0.031433079 0.021663186 0.001292795
## 25 26 27 28 29 30
## 1 -0.01194371 -0.002284283 0.01179768 -0.023898157 0.013976925 0.013259614
## 2 0.04795488 0.024250150 0.02106475 0.018973532 0.011418213 0.010612304
## 3 0.06707305 0.032224779 0.02383960 0.031349896 0.010165523 0.009283604
## 4 0.03317782 0.018183130 0.01895582 0.009663407 0.012471835 0.011734023
## 5 0.05957059 0.021251731 0.01984841 0.005758814 0.003741458 0.002132290
## 6 -0.01505028 0.008717883 0.01589726 0.006600067 0.025023536 0.025505596
## 31 32 33 34 35 36
## 1 0.012329555 0.04985821 0.101590245 0.03172458 0.036520858 -0.05323217
## 2 0.013023069 0.02235703 -0.002459239 0.02271828 0.014284066 0.04303602
## 3 0.012812518 0.01456422 -0.033971519 0.02030431 0.007511492 0.07237982
## 4 0.013270384 0.02818749 0.021565188 0.02449392 0.019455197 0.02062599
## 5 0.006044635 0.03324399 0.005323525 0.02855766 0.015322030 0.03893376
## 6 0.023104686 0.02663125 0.064489046 0.02066168 0.029542263 -0.02361501
## 37 38 39 40 41
## 1 0.047985819 -0.014864749 0.0414630703 -0.0063632555 -0.032135147
## 2 0.009886335 0.022211056 0.0094694781 0.0334902728 0.026997840
## 3 -0.001754963 0.033111156 -0.0004295475 0.0458995198 0.044584947
## 4 0.018782624 0.013968820 0.0170595586 0.0239596621 0.013656140
## 5 0.011047384 0.014025783 0.0084124945 0.0360965286 0.017274706
## 6 0.036967344 0.006581373 0.0352988620 -0.0006447671 -0.002994251
## 42 43 44 45 46 47
## 1 -0.04696173 -0.004609469 0.025587799 0.045581566 0.061098162 0.055332259
## 2 0.04144160 0.030277070 0.010640108 0.005457324 0.003883744 0.009500761
## 3 0.06840804 0.041047083 0.005750853 -0.007047073 -0.013668423 -0.004403881
## 4 0.02084306 0.022024029 0.014442341 0.015063192 0.017311502 0.020106415
## 5 0.03800331 0.031032591 0.005792902 0.002654548 0.004469558 0.012530684
## 6 -0.02026402 0.002715590 0.029324621 0.040096021 0.046311282 0.039595255
## 48 49 50 51
## 1 0.01401646 -0.12672404 0.01663349 0.16948658
## 2 0.01664618 0.05895605 0.01785851 0.02544184
## 3 0.01722273 0.11518891 0.01810399 -0.01591022
## 4 0.01625200 0.01608548 0.01769726 0.05649885
## 5 0.01282831 0.04503522 0.01569963 0.07365188
## 6 0.02045805 -0.06046665 0.02021236 0.06122479#Matriz M
n <- nrow(matriz_x_2)
matriz_M_2 <- diag(n) - matriz_P_2
head(matriz_M_2)## 1 2 3 4 5 6
## 1 0.838388923 0.0127796253 0.06530809 -0.02720791 -0.004995312 -0.0922377599
## 2 0.012779625 0.9685349231 -0.04501952 -0.02109951 -0.030700881 0.0008717607
## 3 0.065308090 -0.0450195150 0.92144105 -0.01942366 -0.038838489 0.0291165550
## 4 -0.027207907 -0.0210995096 -0.01942366 0.97765879 -0.024424173 -0.0206710383
## 5 -0.004995312 -0.0307008811 -0.03883849 -0.02442417 0.965417364 -0.0053388207
## 6 -0.092237760 0.0008717607 0.02911656 -0.02067104 -0.005338821 0.9398166940
## 7 8 9 10 11 12
## 1 -0.054323132 -0.069626967 0.04201951 -0.074183205 -0.033001099 -0.003083400
## 2 -0.001455597 -0.003098691 -0.03662700 -0.009945418 -0.003418230 -0.013002220
## 3 0.014989380 0.017199893 -0.06046699 0.009262056 0.006160696 -0.015462090
## 4 -0.014082445 -0.018604926 -0.01844742 -0.024537798 -0.010848882 -0.011239145
## 5 0.001730668 -0.005605850 -0.03109378 -0.018826182 0.004571400 -0.003299178
## 6 -0.046325314 -0.049657601 0.01450742 -0.045082769 -0.037959510 -0.020240409
## 13 14 15 16 17 18
## 1 0.016405789 -0.03215008 -0.029639461 0.005512265 0.07276090 0.02659707
## 2 -0.022207584 -0.01628493 -0.013464255 -0.020623577 -0.04701342 -0.05395399
## 3 -0.033552760 -0.01148264 -0.008395947 -0.028256192 -0.08341328 -0.07942810
## 4 -0.013630280 -0.01994557 -0.017363227 -0.014862970 -0.01923696 -0.03431040
## 5 -0.013568208 -0.01751464 -0.011882559 -0.014010488 -0.04011594 -0.06569084
## 6 -0.006103986 -0.02642762 -0.028114813 -0.010887113 0.03318595 0.02487159
## 19 20 21 22 23 24
## 1 -0.050098243 -0.091879085 -0.041928113 -0.051718351 -0.012223150 0.013749255
## 2 -0.007076090 0.001274712 -0.008264093 -0.017535492 -0.014631413 -0.028647885
## 3 0.006166430 0.029557504 0.002194011 -0.007506379 -0.015017951 -0.041491243
## 4 -0.017215896 -0.020302131 -0.016291379 -0.025114767 -0.014407468 -0.018855703
## 5 -0.006788032 -0.004534238 -0.006456323 -0.025419303 -0.008805392 -0.025526380
## 6 -0.040086662 -0.060424327 -0.036499323 -0.031433079 -0.021663186 -0.001292795
## 25 26 27 28 29 30
## 1 0.01194371 0.002284283 -0.01179768 0.023898157 -0.013976925 -0.013259614
## 2 -0.04795488 -0.024250150 -0.02106475 -0.018973532 -0.011418213 -0.010612304
## 3 -0.06707305 -0.032224779 -0.02383960 -0.031349896 -0.010165523 -0.009283604
## 4 -0.03317782 -0.018183130 -0.01895582 -0.009663407 -0.012471835 -0.011734023
## 5 -0.05957059 -0.021251731 -0.01984841 -0.005758814 -0.003741458 -0.002132290
## 6 0.01505028 -0.008717883 -0.01589726 -0.006600067 -0.025023536 -0.025505596
## 31 32 33 34 35 36
## 1 -0.012329555 -0.04985821 -0.101590245 -0.03172458 -0.036520858 0.05323217
## 2 -0.013023069 -0.02235703 0.002459239 -0.02271828 -0.014284066 -0.04303602
## 3 -0.012812518 -0.01456422 0.033971519 -0.02030431 -0.007511492 -0.07237982
## 4 -0.013270384 -0.02818749 -0.021565188 -0.02449392 -0.019455197 -0.02062599
## 5 -0.006044635 -0.03324399 -0.005323525 -0.02855766 -0.015322030 -0.03893376
## 6 -0.023104686 -0.02663125 -0.064489046 -0.02066168 -0.029542263 0.02361501
## 37 38 39 40 41
## 1 -0.047985819 0.014864749 -0.0414630703 0.0063632555 0.032135147
## 2 -0.009886335 -0.022211056 -0.0094694781 -0.0334902728 -0.026997840
## 3 0.001754963 -0.033111156 0.0004295475 -0.0458995198 -0.044584947
## 4 -0.018782624 -0.013968820 -0.0170595586 -0.0239596621 -0.013656140
## 5 -0.011047384 -0.014025783 -0.0084124945 -0.0360965286 -0.017274706
## 6 -0.036967344 -0.006581373 -0.0352988620 0.0006447671 0.002994251
## 42 43 44 45 46 47
## 1 0.04696173 0.004609469 -0.025587799 -0.045581566 -0.061098162 -0.055332259
## 2 -0.04144160 -0.030277070 -0.010640108 -0.005457324 -0.003883744 -0.009500761
## 3 -0.06840804 -0.041047083 -0.005750853 0.007047073 0.013668423 0.004403881
## 4 -0.02084306 -0.022024029 -0.014442341 -0.015063192 -0.017311502 -0.020106415
## 5 -0.03800331 -0.031032591 -0.005792902 -0.002654548 -0.004469558 -0.012530684
## 6 0.02026402 -0.002715590 -0.029324621 -0.040096021 -0.046311282 -0.039595255
## 48 49 50 51
## 1 -0.01401646 0.12672404 -0.01663349 -0.16948658
## 2 -0.01664618 -0.05895605 -0.01785851 -0.02544184
## 3 -0.01722273 -0.11518891 -0.01810399 0.01591022
## 4 -0.01625200 -0.01608548 -0.01769726 -0.05649885
## 5 -0.01282831 -0.04503522 -0.01569963 -0.07365188
## 6 -0.02045805 0.06046665 -0.02021236 -0.06122479Compruebe que los residuos en el objeto “modelo_estimado” son iguales al producto de M y, donde “y” es la variable endógena en el modelo (“crime”)
options(scipen = 99999999)
library(magrittr)
residuos_modelo_estimado <- modelo_estimado_1$residuals
datos_modelo_1 <- modelo_estimado_1$model
residuos_matrices_2 <- matriz_M_2 %*% datos_modelo_1$crime
cbind(
residuos_matrices_2,
residuos_modelo_estimado,
residuos_modelo_estimado - residuos_matrices_2
) %>% round(digits = 2) %>% as.data.frame() -> comparacion_2
names(comparacion_2) <- c("por_matrices", "En_modelo", "Diferencia")
print(comparacion_2)## por_matrices En_modelo Diferencia
## 1 -311.71 -311.71 0
## 2 116.80 116.80 0
## 3 45.25 45.25 0
## 4 -34.45 -34.45 0
## 5 243.00 243.00 0
## 6 -145.12 -145.12 0
## 7 86.13 86.13 0
## 8 88.31 88.31 0
## 9 689.82 689.82 0
## 10 -163.29 -163.29 0
## 11 60.90 60.90 0
## 12 126.92 126.92 0
## 13 -19.27 -19.27 0
## 14 322.59 322.59 0
## 15 -22.44 -22.44 0
## 16 128.18 128.18 0
## 17 -70.82 -70.82 0
## 18 -227.95 -227.95 0
## 19 287.10 287.10 0
## 20 303.88 303.88 0
## 21 -341.99 -341.99 0
## 22 -107.18 -107.18 0
## 23 -30.63 -30.63 0
## 24 189.45 189.45 0
## 25 -811.14 -811.14 0
## 26 -351.77 -351.77 0
## 27 102.71 102.71 0
## 28 -23.36 -23.36 0
## 29 73.38 73.38 0
## 30 -91.63 -91.63 0
## 31 324.03 324.03 0
## 32 -115.85 -115.85 0
## 33 113.65 113.65 0
## 34 217.94 217.94 0
## 35 -112.70 -112.70 0
## 36 21.38 21.38 0
## 37 -88.91 -88.91 0
## 38 99.42 99.42 0
## 39 -102.65 -102.65 0
## 40 217.88 217.88 0
## 41 -84.09 -84.09 0
## 42 137.78 137.78 0
## 43 48.89 48.89 0
## 44 -67.16 -67.16 0
## 45 -39.29 -39.29 0
## 46 -415.78 -415.78 0
## 47 -145.50 -145.50 0
## 48 -183.61 -183.61 0
## 49 -138.39 -138.39 0
## 50 -232.91 -232.91 0
## 51 434.17 434.17 0Muestre que los autovalores de x’x son positivos (use el comando eigen)
descomposicion_2 <- eigen(matriz_xx_2)
autovalores_2 <- descomposicion_2$values
print(autovalores_2)## [1] 17956.580914 279.157317 1.681762print(autovalores_2 > 0)## [1] TRUE TRUE TRUE···Ejercicio 4··· Carga de datos
library(readxl)
Investiment_Equation <- read_excel("C:/Users/Keiry/Documents/Eco22/Investiment_Equation.xlsx")Estima la ecuación de inversión, presenta sus resultados en formato APA.
ecuacion_inversion <-
lm(formula = InvReal ~ Trend + Inflation + PNBr + Interest,
data = Investiment_Equation)
library(stargazer)##
## Please cite as:## Hlavac, Marek (2018). stargazer: Well-Formatted Regression and Summary Statistics Tables.## R package version 5.2.2. https://CRAN.R-project.org/package=stargazerstargazer(
ecuacion_inversion,
title = "Ecuacion de Inversion",
type = "text",
digits = 8)##
## Ecuacion de Inversion
## ===============================================
## Dependent variable:
## ---------------------------
## InvReal
## -----------------------------------------------
## Trend -0.01637845***
## (0.00194114)
##
## Inflation 0.00002291
## (0.00133035)
##
## PNBr 0.66454700***
## (0.05411848)
##
## Interest -0.24032170*
## (0.12033660)
##
## Constant -0.50335230***
## (0.05423952)
##
## -----------------------------------------------
## Observations 15
## R2 0.97299900
## Adjusted R2 0.96219860
## Residual Std. Error 0.00662875 (df = 10)
## F Statistic 90.08923000*** (df = 4; 10)
## ===============================================
## Note: *p<0.1; **p<0.05; ***p<0.01Calcule los residuos a través de la matriz M
model.matrix(ecuacion_inversion) -> matriz_x_3
n <- nrow(matriz_x_3)
matriz_M_3 <-
diag(n) - (matriz_x_3 %*% (solve(t(matriz_x_3) %*% matriz_x_3)) %*% t(matriz_x_3))
print(matriz_M_3)## 1 2 3 4 5 6
## 1 0.67842756 -0.28471424 -0.209833694 -0.13923274 -0.1393226219 -0.16147365
## 2 -0.28471424 0.73908208 -0.203548351 -0.12621852 -0.1010834681 -0.13420892
## 3 -0.20983369 -0.20354835 0.758582327 -0.17225535 -0.0801426018 -0.03646669
## 4 -0.13923274 -0.12621852 -0.172255351 0.82801107 -0.1302644807 -0.04228856
## 5 -0.13932262 -0.10108347 -0.080142602 -0.13026448 0.7980613342 -0.12428885
## 6 -0.16147365 -0.13420892 -0.036466690 -0.04228856 -0.1242888510 0.82271472
## 7 -0.04075884 -0.07835320 -0.100105925 -0.05736545 0.0498420966 -0.01917733
## 8 0.12675799 0.06204480 -0.097374051 -0.12684820 0.0557105136 0.11221127
## 9 0.02887486 0.04215174 -0.026124109 -0.12275203 -0.1659655377 -0.02680105
## 10 0.05649707 0.07518229 0.085751775 -0.04969122 -0.1726641302 -0.10543435
## 11 0.03013955 0.03858522 0.128917726 0.03988953 -0.0952374400 -0.16120800
## 12 -0.01835770 -0.02572103 0.085215645 0.08602415 0.0006200257 -0.15295675
## 13 0.01384862 -0.01931307 -0.006215429 0.04595314 0.0718810049 -0.03794411
## 14 -0.01079919 -0.04723036 -0.043188000 0.05457573 0.1029397996 -0.01791431
## 15 0.06994704 0.06334503 -0.083213272 -0.08753708 -0.0700856433 0.08523657
## 7 8 9 10 11
## 1 -0.04075884 0.1267579909 0.02887486 0.05649707 0.0301395482
## 2 -0.07835320 0.0620447953 0.04215174 0.07518229 0.0385852240
## 3 -0.10010592 -0.0973740506 -0.02612411 0.08575177 0.1289177256
## 4 -0.05736545 -0.1268481966 -0.12275203 -0.04969122 0.0398895251
## 5 0.04984210 0.0557105136 -0.16596554 -0.17266413 -0.0952374400
## 6 -0.01917733 0.1122112748 -0.02680105 -0.10543435 -0.1612080000
## 7 0.72908167 -0.3412372203 0.03848329 0.03284320 -0.0331689311
## 8 -0.34123722 0.2961643473 -0.11673072 -0.06805334 -0.0008186063
## 9 0.03848329 -0.1167307207 0.73613120 -0.24227787 -0.0995979798
## 10 0.03284320 -0.0680533391 -0.24227787 0.65892407 -0.2706620648
## 11 -0.03316893 -0.0008186063 -0.09959798 -0.27066206 0.6637732682
## 12 -0.08204746 0.0689687040 0.04180083 -0.09942102 -0.2561204399
## 13 -0.12947696 -0.0577740589 0.04943069 0.02953218 -0.0824169036
## 14 -0.10565511 0.0249327305 0.09038480 0.11932553 -0.0060307187
## 15 0.13709616 0.0620458361 -0.22700810 -0.04985211 0.1039557933
## 12 13 14 15
## 1 -0.0183577019 0.013848624 -0.010799191 0.06994704
## 2 -0.0257210317 -0.019313067 -0.047230364 0.06334503
## 3 0.0852156449 -0.006215429 -0.043188000 -0.08321327
## 4 0.0860241509 0.045953139 0.054575734 -0.08753708
## 5 0.0006200257 0.071881005 0.102939800 -0.07008564
## 6 -0.1529567464 -0.037944112 -0.017914310 0.08523657
## 7 -0.0820474556 -0.129476957 -0.105655109 0.13709616
## 8 0.0689687040 -0.057774059 0.024932730 0.06204584
## 9 0.0418008317 0.049430688 0.090384796 -0.22700810
## 10 -0.0994210180 0.029532177 0.119325528 -0.04985211
## 11 -0.2561204399 -0.082416904 -0.006030719 0.10395579
## 12 0.6834362759 -0.205933791 -0.201122369 0.07561492
## 13 -0.2059337907 0.748638334 -0.304841907 -0.11536774
## 14 -0.2011223686 -0.304841907 0.583886260 -0.23926288
## 15 0.0756149198 -0.115367741 -0.239262879 0.27508548Y<-Investiment_Equation$InvReal
residuos<-matriz_M_3%*%Y
print(residuos)## [,1]
## 1 -0.0100602233
## 2 -0.0009290882
## 3 0.0029656679
## 4 0.0078576839
## 5 0.0028109133
## 6 0.0006259732
## 7 0.0075909286
## 8 -0.0055352778
## 9 -0.0037254127
## 10 0.0006953129
## 11 0.0019904770
## 12 -0.0001288433
## 13 -0.0101976729
## 14 0.0068712384
## 15 -0.0008316770Calcule un intervalo de confianza del 93% para el impacto del PNBr en la Inversión, e interprételo.
confint(object = ecuacion_inversion,parm = "PNBr",level = .93)## 3.5 % 96.5 %
## PNBr 0.554777 0.774317#conforme a los datos presentados, el PNBr tiene un 77% sobre el nivel de la inversion. ···Ejercicio 5 Carga de datos
load("C:/Users/Keiry/Documents/Eco22/consumption_equation.RData")Calcule los residuos del modelo.
n<-nrow(P)
M<-diag(n)-P
residuos<-M%*%C
print(residuos)## [,1]
## 1 -5.859103
## 2 2.605057
## 3 45.765735
## 4 31.102448
## 5 -21.037889
## 6 7.008120
## 7 17.859663
## 8 10.705631
## 9 22.002328
## 10 -2.689665
## 11 7.784083
## 12 -13.127696
## 13 17.521565
## 14 17.304695
## 15 -16.308260
## 16 -5.255508
## 17 2.788211
## 18 -16.379339
## 19 -14.327554
## 20 11.749135
## 21 -31.424669
## 22 -23.329596
## 23 22.171806
## 24 -5.040038
## 25 -36.191398
## 26 -25.211753
## 27 -21.411271
## 28 1.410519
## 29 -24.229564
## 30 20.971808
## 31 43.342653
## 32 36.808458
## 33 17.882297
## 34 -33.100273
## 35 -37.819995
## 36 -49.370820
## 37 23.456143
## 38 -25.510341
## 39 -11.960629
## 40 -9.234201
## 41 21.949616
## 42 3.211123
## 43 -14.511436
## 44 3.197576
## 45 -62.396763
## 46 -66.854500
## 47 8.330745
## 48 91.963380
## 49 61.620735
## 50 48.148861
## 51 -10.717721
## 52 -84.069717
## 53 -56.426627
## 54 125.113605Calcule la varianza del error del modelo.
#Sigma cuadrado
k<-4
var_error=t(residuos)%*%residuos/(n-k)
print(var_error)## [,1]
## [1,] 1428.746Obtenga la matriz de Var-Cov del modelo.
var_error<-as.vector(var_error)
var.cov<-var_error*solve(XX)
print(var.cov)## (Intercept) Yd W I
## (Intercept) 164.522304918 -0.09333539523 0.009670913575 10.5186890800
## Yd -0.093335395 0.00018911268 -0.000032769561 -0.0072901023
## W 0.009670914 -0.00003276956 0.000006165749 0.0004193421
## I 10.518689080 -0.00729010228 0.000419342092 5.3203789879Obtenga las estimaciones del Consumo, del modelo propuesto.
C_estimada<-P%*%C
cuadro<-as.data.frame(cbind(C,C_estimada,residuos))
names(cuadro)<-c("C","C_estimada","Residuos")
print(head(cuadro))## C C_estimada Residuos
## 1 976.4 982.2591 -5.859103
## 2 998.1 995.4949 2.605057
## 3 1025.3 979.5343 45.765735
## 4 1090.9 1059.7976 31.102448
## 5 1107.1 1128.1379 -21.037889
## 6 1142.4 1135.3919 7.008120···Ejercicio 6··· Carga de datos
load("C:/Users/Keiry/Documents/Eco22/datos_ventas.RData")Estima la ecuación de ventas, presenta sus resultados en formato APA.
options(scipen = 99999999)
ecuacion_ventas <-
lm(formula = ventas ~.,
data = datos_ventas)
library(stargazer)
stargazer(ecuacion_ventas,title = "Ecuacion Ventas", type = "text",digits = 9)##
## Ecuacion Ventas
## ==================================================
## Dependent variable:
## ------------------------------
## ventas
## --------------------------------------------------
## tv 0.045033770
## (0.117959000)
##
## radio -3.449593000***
## (0.206123400)
##
## periodico 18.485040000***
## (0.563420000)
##
## Constant -33.288540000***
## (7.172245000)
##
## --------------------------------------------------
## Observations 200
## R2 0.846668100
## Adjusted R2 0.844321200
## Residual Std. Error 33.874780000 (df = 196)
## F Statistic 360.757500000*** (df = 3; 196)
## ==================================================
## Note: *p<0.1; **p<0.05; ***p<0.01Calcule los residuos a través de la matriz M
options(scipen = 99999999)
model.matrix(ecuacion_ventas) -> matriz_x_4
n <- nrow(matriz_x_4)
matriz_M_4<-
diag(n) - (matriz_x_4 %*% (solve(t(matriz_x_4) %*% matriz_x_4)) %*% t(matriz_x_4))
print(matriz_M_4)## 1 2 3 4 5
## 1 0.97175346136 -0.00323509620 -0.00973715187 -0.01893120752 -0.01539677375
## 2 -0.00323509620 0.97545667536 -0.03344231907 -0.01165061515 -0.00078455158
## 3 -0.00973715187 -0.03344231907 0.94960551342 -0.01853895086 -0.00670915966
## 4 -0.01893120752 -0.01165061515 -0.01853895086 0.98326718427 -0.00782642137
## 5 -0.01539677375 -0.00078455158 -0.00670915966 -0.00782642137 0.97680930146
## 6 -0.00856326584 -0.04007984887 -0.06047340454 -0.02017348277 -0.00669081426
## 7 0.00191577224 -0.01537028952 -0.01668511765 -0.00542784026 0.00402383162
## 8 0.00259221130 -0.00231397915 0.00255094222 0.00033728339 0.00103696247
## 9 0.01556614639 -0.00506809458 -0.00064169169 0.00881350319 -0.00173469402
## 10 0.00030196859 0.00388942771 0.00718752163 0.00303981441 -0.01168939645
## 11 0.00235923949 -0.00246070322 -0.00187293224 0.00193886551 -0.01047389770
## 12 0.00025770055 0.00327381661 0.01236755317 0.00009754086 0.00530155454
## 13 -0.00981538978 -0.02569864079 -0.04010599916 -0.01499797642 -0.01136929617
## 14 0.00735344943 -0.00013418276 0.00530424759 0.00506890569 -0.00278359091
## 15 -0.01615652627 -0.00365578709 -0.00562684538 -0.01188572479 -0.00756243252
## 16 -0.02132083076 -0.00822639375 -0.01193532070 -0.01787307134 -0.00316221109
## 17 -0.03179281618 -0.02468310066 -0.04931300052 -0.02678452268 -0.03148675048
## 18 -0.02621149530 0.00106882555 -0.00065079766 -0.01683965842 -0.00958488529
## 19 0.00284109851 -0.00717243551 -0.00552361877 -0.00102300649 -0.00060906831
## 20 -0.00149022654 -0.00333754676 -0.00009272696 -0.00271187535 -0.00009113127
## 21 -0.01821892088 -0.00254245628 -0.00628280421 -0.01201803743 -0.01323479167
## 22 -0.00279447243 0.00555202112 0.00920988089 0.00151721084 -0.01184562381
## 23 -0.00151945933 -0.01757233499 -0.02726386352 -0.00574377415 -0.01430160789
## 24 -0.00627631994 0.00270730945 0.00590366278 -0.00268583076 -0.00727261993
## 25 0.00395084889 -0.00464606375 -0.00286074532 0.00130712855 -0.00455084997
## 26 -0.00085939128 0.00607932413 0.01066492560 0.00291829913 -0.01093251553
## 27 0.00108629477 -0.00581859369 -0.00149482472 -0.00271556826 0.00551670427
## 28 -0.00563553472 0.00390386845 0.00826336646 -0.00197399335 -0.00615057787
## 29 -0.00831464338 0.00228657723 0.00710284865 -0.00521502735 -0.00125148316
## 30 -0.00495007378 -0.00750051937 -0.01146252824 -0.00475171734 -0.01219615414
## 31 -0.01902240258 0.00443128884 0.00563029313 -0.01054930699 -0.00978107035
## 32 -0.00585982418 -0.00562012231 -0.00824720858 -0.00488917282 -0.01095013110
## 33 -0.00171914289 0.00198083388 0.00248850721 0.00154616706 -0.01562549463
## 34 0.00107550513 0.00642745331 0.01711577757 0.00194793754 0.00457300378
## 35 0.00671183887 0.00384927180 0.01009542586 0.00664789612 -0.00630253735
## 36 0.00217530889 0.00815266184 0.01603097856 0.00507084355 -0.00630396624
## 37 -0.00832995509 0.00448193427 0.01581878624 -0.00674096518 0.01347225826
## 38 -0.00794749938 -0.02351591198 -0.03113762839 -0.01520161702 0.00327500213
## 39 -0.00085849135 -0.01532857322 -0.01984253824 -0.00613392409 -0.00366658553
## 40 -0.01376673802 -0.00103770444 0.00158535582 -0.01046564878 0.00012679025
## 41 -0.00902866321 0.00051729345 0.00224055022 -0.00548806018 -0.00681363815
## 42 -0.01081518678 -0.00699936587 -0.00853299629 -0.01001126245 -0.00364418716
## 43 -0.00293008259 0.00716062039 0.01857095863 -0.00099676711 0.00722964995
## 44 -0.00395834290 0.00372843195 0.00639473023 -0.00005290824 -0.01131133836
## 45 -0.00182760470 -0.01840217461 -0.02599622097 -0.00740238895 -0.00710330354
## 46 -0.00664749502 -0.00286545299 -0.00235960426 -0.00518674058 -0.00610751834
## 47 -0.00403866708 -0.00254778128 -0.00414589476 -0.00207066269 -0.01356402271
## 48 -0.01060587054 0.00071389913 0.00739466420 -0.00874648999 0.00730420065
## 49 -0.01418391459 0.00006099001 -0.00313905782 -0.00757160094 -0.01746847947
## 50 -0.00297217464 -0.00563786034 -0.00844967899 -0.00260217915 -0.01271036003
## 51 -0.00564683913 0.00388613350 0.00423811327 -0.00024157823 -0.01720873342
## 52 0.00758497094 0.00068047912 0.00743093176 0.00516898565 -0.00048989093
## 53 -0.01751768446 -0.00243152654 -0.00161940635 -0.01340224563 -0.00111469202
## 54 -0.02202069708 -0.00997053978 -0.01577866343 -0.01855438468 -0.00601852190
## 55 -0.00728282342 0.00418611401 0.01144811979 -0.00433575602 0.00218160705
## 56 -0.02547246441 -0.00756773345 -0.01244548505 -0.02014867507 -0.00556063592
## 57 0.00328563943 -0.02566732631 -0.03529855433 -0.00700829928 -0.00398841049
## 58 0.00069986794 -0.00247120461 0.00117656689 -0.00067921447 -0.00125683132
## 59 -0.01738371140 -0.00555542827 -0.00467762127 -0.01522959198 0.00374273691
## 60 -0.00230800985 0.00083071567 0.00838961875 -0.00268846068 0.00589082482
## 61 0.00355485979 -0.00048359757 0.00107964059 0.00363384072 -0.01129943215
## 62 -0.02511413629 -0.00140845151 -0.00348924468 -0.01734715586 -0.00731444923
## 63 -0.00714316215 0.00398267944 0.00726561600 -0.00261290502 -0.00858306323
## 64 0.00403409136 -0.00757292283 -0.00293313254 -0.00165834815 0.00774776251
## 65 -0.00716467913 -0.01106208619 -0.01096079355 -0.01039618162 0.00542497718
## 66 0.01044522130 -0.00154639593 0.00494758369 0.00612162269 0.00091181268
## 67 0.01176934350 -0.01209559646 -0.00826371468 0.00188077046 0.00894916993
## 68 0.00214270811 0.00179731978 0.00798733357 0.00191541668 -0.00132892027
## 69 -0.00388571633 0.00305104011 0.01085328816 -0.00265465447 0.00389603075
## 70 -0.01225193749 -0.00346922364 -0.00004734965 -0.01113188473 0.00535345634
## 71 -0.01283059315 -0.00272553341 -0.00295226413 -0.00952848834 -0.00561487256
## 72 -0.00442514952 -0.00186524667 -0.00186668954 -0.00264992311 -0.01000928636
## 73 0.00757622841 -0.02087761960 -0.02328467295 -0.00395673866 0.00684762114
## 74 -0.00353589143 0.00157360031 0.00206670480 -0.00009017861 -0.01424584625
## 75 -0.00246104619 0.00128402449 0.00766316784 -0.00201429874 0.00200661390
## 76 -0.01660678045 -0.03480292933 -0.05697973819 -0.02235744350 -0.01606975360
## 77 0.00539368676 -0.00243341292 -0.00148075915 0.00412570895 -0.01084628409
## 78 0.00148011072 -0.00692327958 -0.00345021554 -0.00271373656 0.00466289135
## 79 0.01556620432 -0.02450613038 -0.02636728263 -0.00026960205 0.01032761664
## 80 -0.00025020445 0.00088123647 0.00315338173 0.00123331059 -0.00972506546
## 81 0.00152976871 -0.01095195765 -0.01097388197 -0.00359999471 0.00107545088
## 82 -0.00758356763 0.00469738247 0.00493921114 -0.00118657696 -0.01788741249
## 83 -0.00240623680 -0.00828071170 -0.01023978482 -0.00414913047 -0.00659488194
## 84 -0.00339953919 -0.02126577257 -0.02629030021 -0.01147557779 0.00504220951
## 85 -0.01398240741 -0.00456086610 -0.00311286352 -0.01226207185 0.00231033997
## 86 -0.02018501236 -0.00240296622 -0.00978844739 -0.01184915378 -0.02266470105
## 87 0.00368163645 -0.01058075667 -0.00897444267 -0.00243370586 0.00406786258
## 88 -0.01734616983 -0.01634896442 -0.02610958640 -0.01712010141 -0.00935404906
## 89 -0.01891779376 -0.01249759405 -0.02464184522 -0.01494043857 -0.02109332411
## 90 -0.01298611445 -0.01906263489 -0.02646272274 -0.01645630182 -0.00063514288
## 91 0.00417066624 0.00445769309 0.01086219221 0.00499799397 -0.00566370989
## 92 0.00031314694 -0.00268043894 -0.00457987923 0.00132148325 -0.01611966086
## 93 -0.02139948198 -0.00445931982 -0.00957498348 -0.01502551678 -0.01273002598
## 94 -0.02969875172 -0.00239762253 -0.00941317047 -0.01931192891 -0.01744545208
## 95 0.00440748289 -0.00154329822 0.00319485141 0.00225550940 -0.00128403755
## 96 -0.01600685714 -0.00735880553 -0.01238433113 -0.01268954591 -0.01046860324
## 97 0.00454918483 0.00670264269 0.01456096752 0.00601954696 -0.00521041159
## 98 -0.00417636019 0.00017821518 0.00378900710 -0.00279416545 -0.00322029624
## 99 -0.02551743429 0.00147658995 0.00121227560 -0.01669476975 -0.00648231154
## 100 -0.01247290330 -0.01330995436 -0.01795872640 -0.01376341086 -0.00196741869
## 101 -0.01148089081 0.00227360127 -0.00125113097 -0.00400758256 -0.02291492762
## 102 -0.04242080239 -0.00171421573 -0.01488959911 -0.02597070770 -0.02990621669
## 103 -0.00447963040 0.00659906828 0.01162571713 0.00026236755 -0.00890017384
## 104 -0.00209389991 0.00169617267 0.00640202918 -0.00075006747 -0.00341079306
## 105 -0.00332180789 0.00218637396 0.01163343868 -0.00346705288 0.00950914145
## 106 -0.01937764431 -0.01396204359 -0.02130377578 -0.01828431732 -0.00538045492
## 107 0.00295078875 -0.00929774561 -0.01195690042 -0.00034921477 -0.00935771271
## 108 0.00184475969 0.00170701014 0.00351072156 0.00354916688 -0.01319863407
## 109 0.00561060249 -0.00507519559 -0.00632435821 0.00364674519 -0.01303111976
## 110 -0.00317195940 0.00567993804 0.01563001284 -0.00144539449 0.00553977358
## 111 -0.01573240414 0.00217679487 -0.00248468913 -0.00683373689 -0.02403541612
## 112 -0.01089992825 0.00009819725 0.00514235582 -0.00863158564 0.00383834764
## 113 0.00417801205 0.00318575381 0.01172848100 0.00329468788 0.00217803518
## 114 -0.00062172802 0.00222021840 0.00907727295 -0.00024120192 0.00109746651
## 115 -0.00404639030 -0.02088322549 -0.02528506659 -0.01201156196 0.00647136341
## 116 -0.00961092769 -0.01796597649 -0.02655186241 -0.01267905468 -0.00707011810
## 117 -0.00191004056 -0.00171078372 -0.00029092107 -0.00124621624 -0.00742151219
## 118 0.00404639688 0.00343104909 0.00780589357 0.00516494026 -0.00966940969
## 119 -0.02359350507 -0.01533232088 -0.02866816013 -0.01973485301 -0.01802830702
## 120 0.00716703925 -0.01332863667 -0.01532571649 0.00014487871 -0.00327893273
## 121 -0.01228631503 -0.00605214018 -0.00958188478 -0.00969157197 -0.00995372641
## 122 -0.00293544048 -0.01906677250 -0.02890312858 -0.00767725348 -0.01181164560
## 123 0.00097041588 0.00643550959 0.01191367672 0.00414978130 -0.00981087478
## 124 0.00160586703 -0.00916574451 -0.00550432981 -0.00406449131 0.00852741925
## 125 -0.02755896914 -0.00437504207 -0.01297976590 -0.01817800811 -0.01979150408
## 126 -0.00017834659 -0.00302863603 -0.00242139385 -0.00036361044 -0.00843797988
## 127 -0.00013143313 -0.03200958537 -0.04496026307 -0.01204118297 -0.00205165394
## 128 0.00681446081 0.00334237238 0.00885468408 0.00673894015 -0.00761034785
## 129 -0.00600895060 -0.00037437306 0.01008546010 -0.00753158188 0.01738037593
## 130 -0.00524750639 -0.00640439575 -0.01087968662 -0.00408849330 -0.01514652009
## 131 0.02218234652 -0.03837631442 -0.04425991761 -0.00187420297 0.01729575287
## 132 -0.01053401627 0.00577369465 0.00493048358 -0.00232235917 -0.02121774875
## 133 0.01733847753 -0.02119003930 -0.02045883605 0.00197631142 0.01169223515
## 134 -0.01656217448 -0.00285367430 -0.00426360941 -0.01195422357 -0.00704614761
## 135 -0.01141148563 -0.02508779263 -0.03884405213 -0.01613621263 -0.00978812686
## 136 0.00962819981 -0.02447203734 -0.02437763652 -0.00566271027 0.01831125420
## 137 0.01111184856 -0.02290129484 -0.02321542121 -0.00338893257 0.01414443663
## 138 -0.02418892147 0.00140788645 -0.00214714494 -0.01427806478 -0.01607160229
## 139 0.00508184902 -0.01443401605 -0.01543212859 -0.00256559008 0.00208225989
## 140 -0.00069663099 -0.00428404643 0.00453527705 -0.00511560486 0.01641917448
## 141 0.00489690142 -0.00498743195 -0.00167387014 0.00115761368 -0.00022233751
## 142 -0.02697172928 -0.00764588789 -0.01746632074 -0.01918663280 -0.01845764437
## 143 -0.01463753883 -0.00105200867 -0.00021165535 -0.01036361402 -0.00440006354
## 144 -0.00385765017 0.00015367310 -0.00057523231 -0.00066730809 -0.01533319196
## 145 -0.00564111069 -0.00476423847 -0.00740437376 -0.00419457913 -0.01238012974
## 146 0.00510095686 0.00488444158 0.01120943160 0.00600675352 -0.00694159932
## 147 0.00199045483 0.00663738772 0.01423244472 0.00413041253 -0.00470947786
## 148 -0.02207234322 -0.00265310049 -0.00223078281 -0.01686361851 0.00015490945
## 149 0.00842395840 -0.02137262340 -0.02156616319 -0.00457482504 0.01334879290
## 150 0.00434997228 -0.01341619084 -0.01406768671 -0.00265948165 0.00182213111
## 151 -0.01147128500 0.00502497375 0.00636461310 -0.00445193508 -0.01362817760
## 152 -0.01038424465 -0.00071949487 -0.00469569874 -0.00479012634 -0.02011225001
## 153 -0.00249646277 0.00134158366 0.00736383848 -0.00185044052 0.00094740119
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## 25 26 27 28 29
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## 30 31 32 33 34
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## 200 0.9859935120Y<-datos_ventas$ventas
residuos<-matriz_M_4%*%Y
print(residuos)## [,1]
## 1 -17.8524638
## 2 19.0821552
## 3 33.7931916
## 4 -17.3508987
## 5 10.2572135
## 6 74.2038531
## 7 -15.2465204
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## 10 45.1613878
## 11 -40.6649446
## 12 8.9590198
## 13 5.1392043
## 14 -22.6236420
## 15 -2.4070766
## 16 -23.2129522
## 17 -8.8531474
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## 22 56.1602254
## 23 -4.4128052
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## 30 -36.8482228
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## 43 39.7209714
## 44 29.5192706
## 45 -12.0296830
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## 52 -31.1473697
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## 56 -38.1989298
## 57 33.9900112
## 58 -9.0293035
## 59 -26.4532617
## 60 5.2080674
## 61 -57.0047861
## 62 -7.9150425
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## 64 -21.0722866
## 65 -22.0009918
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## 83 -31.7292205
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## 95 -24.0859349
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## 97 26.4214991
## 98 3.1212001
## 99 -2.9193041
## 100 -7.6730899
## 101 52.0041912
## 102 10.4210157
## 103 73.7871802
## 104 7.9854131
## 105 6.9306678
## 106 -26.3200156
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## 108 -37.1411765
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## 110 15.2312039
## 111 37.1313178
## 112 2.0545188
## 113 1.3651902
## 114 19.5562302
## 115 1.4943123
## 116 -6.1604300
## 117 -4.8525782
## 118 -61.9776211
## 119 -11.2002151
## 120 -15.1234596
## 121 -21.5609770
## 122 -4.7202419
## 123 50.4386227
## 124 -5.7864987
## 125 6.7136905
## 126 -35.9140143
## 127 50.9977671
## 128 -49.5940852
## 129 -34.1058846
## 130 -46.9621445
## 131 140.6245747
## 132 71.7959550
## 133 30.0581974
## 134 4.3121884
## 135 0.7502335
## 136 28.9102154
## 137 17.3960181
## 138 19.5045244
## 139 -12.7465335
## 140 -13.0911168
## 141 -36.7362018
## 142 -9.2131004
## 143 -4.9409642
## 144 -36.2423122
## 145 -31.9387023
## 146 -10.6584048
## 147 54.1763052
## 148 -25.9962973
## 149 8.2843516
## 150 -20.6385139
## 151 62.6625611
## 152 -33.3544363
## 153 3.7729886
## 154 -11.3760631
## 155 5.0805779
## 156 17.9950120
## 157 -7.8494101
## 158 -0.2201702
## 159 35.3022384
## 160 -11.5540752
## 161 0.6591253
## 162 -5.5871655
## 163 7.5462798
## 164 -9.3303245
## 165 -19.0175482
## 166 55.7263685
## 167 32.0402256
## 168 31.6353338
## 169 11.4108832
## 170 76.5904762
## 171 -32.7991015
## 172 -0.2825814
## 173 -19.0264844
## 174 9.3293014
## 175 54.2493038
## 176 -22.1047290
## 177 11.5543472
## 178 12.5352601
## 179 98.7318828
## 180 -0.3195726
## 181 4.3908269
## 182 43.6649823
## 183 -53.0060931
## 184 -18.3203130
## 185 33.8772333
## 186 -24.7792769
## 187 -11.5610805
## 188 2.7811315
## 189 73.1591927
## 190 -31.1749134
## 191 14.6672356
## 192 -37.2279106
## 193 -45.8529068
## 194 -17.4973688
## 195 -14.2672641
## 196 -56.8557034
## 197 -35.2780738
## 198 5.4730833
## 199 -12.5781921
## 200 46.9637691Calcule un intervalo de confianza del 96.8% para el impacto del gasto de publicidad en TV, en las ventas, e interprételo.
confint(object = ecuacion_ventas,parm = "tv",level = .968)## 1.6 % 98.4 %
## tv -0.2097376 0.2998052#