Caso
2024-04-26
Real.estate <- read.csv("/cloud/project/Real estate.csv")
summary(Real.estate)## No X1.transaction.date X2.house.age
## Min. : 1.0 Min. :2013 Min. : 0.000
## 1st Qu.:104.2 1st Qu.:2013 1st Qu.: 9.025
## Median :207.5 Median :2013 Median :16.100
## Mean :207.5 Mean :2013 Mean :17.713
## 3rd Qu.:310.8 3rd Qu.:2013 3rd Qu.:28.150
## Max. :414.0 Max. :2014 Max. :43.800
## X3.distance.to.the.nearest.MRT.station X4.number.of.convenience.stores
## Min. : 23.38 Min. : 0.000
## 1st Qu.: 289.32 1st Qu.: 1.000
## Median : 492.23 Median : 4.000
## Mean :1083.89 Mean : 4.094
## 3rd Qu.:1454.28 3rd Qu.: 6.000
## Max. :6488.02 Max. :10.000
## X5.latitude X6.longitude Y.house.price.of.unit.area
## Min. :24.93 Min. :121.5 Min. : 7.60
## 1st Qu.:24.96 1st Qu.:121.5 1st Qu.: 27.70
## Median :24.97 Median :121.5 Median : 38.45
## Mean :24.97 Mean :121.5 Mean : 37.98
## 3rd Qu.:24.98 3rd Qu.:121.5 3rd Qu.: 46.60
## Max. :25.01 Max. :121.6 Max. :117.50summary(Real.estate)## No X1.transaction.date X2.house.age
## Min. : 1.0 Min. :2013 Min. : 0.000
## 1st Qu.:104.2 1st Qu.:2013 1st Qu.: 9.025
## Median :207.5 Median :2013 Median :16.100
## Mean :207.5 Mean :2013 Mean :17.713
## 3rd Qu.:310.8 3rd Qu.:2013 3rd Qu.:28.150
## Max. :414.0 Max. :2014 Max. :43.800
## X3.distance.to.the.nearest.MRT.station X4.number.of.convenience.stores
## Min. : 23.38 Min. : 0.000
## 1st Qu.: 289.32 1st Qu.: 1.000
## Median : 492.23 Median : 4.000
## Mean :1083.89 Mean : 4.094
## 3rd Qu.:1454.28 3rd Qu.: 6.000
## Max. :6488.02 Max. :10.000
## X5.latitude X6.longitude Y.house.price.of.unit.area
## Min. :24.93 Min. :121.5 Min. : 7.60
## 1st Qu.:24.96 1st Qu.:121.5 1st Qu.: 27.70
## Median :24.97 Median :121.5 Median : 38.45
## Mean :24.97 Mean :121.5 Mean : 37.98
## 3rd Qu.:24.98 3rd Qu.:121.5 3rd Qu.: 46.60
## Max. :25.01 Max. :121.6 Max. :117.50cor(Real.estate)## No X1.transaction.date
## No 1.00000000 -0.048657949
## X1.transaction.date -0.04865795 1.000000000
## X2.house.age -0.03280811 0.017548767
## X3.distance.to.the.nearest.MRT.station -0.01357349 0.060879953
## X4.number.of.convenience.stores -0.01269895 0.009635445
## X5.latitude -0.01010966 0.035057756
## X6.longitude -0.01105928 -0.041081778
## Y.house.price.of.unit.area -0.02858717 0.087490606
## X2.house.age
## No -0.03280811
## X1.transaction.date 0.01754877
## X2.house.age 1.00000000
## X3.distance.to.the.nearest.MRT.station 0.02562205
## X4.number.of.convenience.stores 0.04959251
## X5.latitude 0.05441990
## X6.longitude -0.04852005
## Y.house.price.of.unit.area -0.21056705
## X3.distance.to.the.nearest.MRT.station
## No -0.01357349
## X1.transaction.date 0.06087995
## X2.house.age 0.02562205
## X3.distance.to.the.nearest.MRT.station 1.00000000
## X4.number.of.convenience.stores -0.60251914
## X5.latitude -0.59106657
## X6.longitude -0.80631677
## Y.house.price.of.unit.area -0.67361286
## X4.number.of.convenience.stores
## No -0.012698946
## X1.transaction.date 0.009635445
## X2.house.age 0.049592513
## X3.distance.to.the.nearest.MRT.station -0.602519145
## X4.number.of.convenience.stores 1.000000000
## X5.latitude 0.444143306
## X6.longitude 0.449099007
## Y.house.price.of.unit.area 0.571004911
## X5.latitude X6.longitude
## No -0.01010966 -0.01105928
## X1.transaction.date 0.03505776 -0.04108178
## X2.house.age 0.05441990 -0.04852005
## X3.distance.to.the.nearest.MRT.station -0.59106657 -0.80631677
## X4.number.of.convenience.stores 0.44414331 0.44909901
## X5.latitude 1.00000000 0.41292394
## X6.longitude 0.41292394 1.00000000
## Y.house.price.of.unit.area 0.54630665 0.52328651
## Y.house.price.of.unit.area
## No -0.02858717
## X1.transaction.date 0.08749061
## X2.house.age -0.21056705
## X3.distance.to.the.nearest.MRT.station -0.67361286
## X4.number.of.convenience.stores 0.57100491
## X5.latitude 0.54630665
## X6.longitude 0.52328651
## Y.house.price.of.unit.area 1.00000000modelo <- lm(X3.distance.to.the.nearest.MRT.station~X6.longitude, data = Real.estate)
coef(modelo)## (Intercept) X6.longitude
## 8059869.41 -66309.25"Intervalos de confianza"## [1] "Intervalos de confianza"confint(modelo)## 2.5 % 97.5 %
## (Intercept) 7487358.15 8632380.67
## X6.longitude -71019.98 -61598.51Supuestos del modelo lineal: 1. Los errores se distribuyen normalmente 2. La media de los errores es cero 3. Los errores independientes
plot(Real.estate$X6.longitude, Real.estate$X3.distance.to.the.nearest.MRT.station, xlab = "lONGITUDE", ylab = "MRT STATION")
abline(modelo)
residuos <- residuals(modelo)
residuos## 1 2 3 4 5
## -542.8713322 -369.5612019 177.5892801 177.5892801 -90.6383189
## 6 7 8 9 10
## -289.4862639 -257.5783717 -204.8767907 1193.5152205 -527.4988134
## 11 12 13 14 15
## -654.8730357 -347.6496491 -325.8263881 -132.7944954 127.2967080
## 16 17 18 19 20
## 345.9981608 -46.9702251 -876.9973278 23.5266277 -552.6461005
## 21 22 23 24 25
## -256.9377872 -5.7587510 1274.7984792 -5.7587510 -239.2223042
## 26 27 28 29 30
## -663.6686233 -0.5328199 -424.9044153 -220.7941406 267.7655952
## 31 32 33 34 35
## 949.7986068 -266.8117071 -519.1294314 -133.6803904 -277.1659038
## 36 37 38 39 40
## 1987.5596981 -394.2364023 1274.7984792 413.0498841 -123.5833956
## 41 42 43 44 45
## 1038.6190193 997.3304134 -284.6710465 68.7135588 397.0775598
## 46 47 48 49 50
## 172.7226034 123.9942749 -191.9066222 1029.8897747 910.6284462
## 51 52 53 54 55
## -235.8842799 1964.8261611 -697.0434042 -325.8263881 -123.5833956
## 56 57 58 59 60
## -140.1569983 -233.2924163 -778.8238420 910.6284462 -680.2691334
## 61 62 63 64 65
## -389.4182003 -41.8479625 -288.6392639 397.0775598 958.8206287
## 66 67 68 69 70
## -301.7640523 -391.0646425 -494.4270766 -308.7444009 177.5892801
## 71 72 73 74 75
## -347.6496491 -191.9066222 -276.8092153 1038.6190193 -421.9228766
## 76 77 78 79 80
## 1274.7984792 -181.7645143 -290.6608357 -501.6815035 1359.3356398
## 81 82 83 84 85
## 397.0775598 -289.7400999 -325.6303717 -37.6123741 47.2910296
## 86 87 88 89 90
## -30.8392858 1408.9168418 997.3304134 -60.7952055 813.0422600
## 91 92 93 94 95
## -993.6199753 -63.8830206 -132.7944954 -110.0328035 -458.8250674
## 96 97 98 99 100
## -494.4270766 -347.6496491 -491.0497852 -123.5833956 -347.6496491
## 101 102 103 104 105
## -69.4762298 -1147.2374098 -391.0646425 -538.7162950 -85.4453566
## 106 107 108 109 110
## -46.9702251 -249.9137940 1274.7984792 -342.2613609 -297.2474902
## 111 112 113 114 115
## -494.4270766 -298.5144605 -224.1660325 -375.0651537 -405.6669422
## 116 117 118 119 120
## 584.2770559 1696.4820566 1155.2792042 -579.0871951 -123.5833956
## 121 122 123 124 125
## -325.8263881 -325.8263881 78.9581296 -1008.6015124 -5.7587510
## 126 127 128 129 130
## -391.0646425 -185.7720275 -0.5328199 -492.8125655 -319.4104930
## 131 132 133 134 135
## -338.2304547 -297.2474902 -251.7499383 -215.8970897 -316.7832625
## 136 137 138 139 140
## 996.1715572 -90.6383189 -140.9169602 -758.1673511 -325.8263881
## 141 142 143 144 145
## -123.5833956 -657.3557767 425.9635496 -325.8263881 1274.7984792
## 146 147 148 149 150
## 267.7655952 -1008.6015124 173.7854034 1282.2560206 -301.7529189
## 151 152 153 154 155
## -294.5613999 -396.4678727 1274.7984792 -457.8010071 997.3304134
## 156 157 158 159 160
## 1038.6190193 -72.5290835 -183.1505294 -90.6383189 -183.1505294
## 161 162 163 164 165
## -755.7978814 -181.7645143 997.3304134 -494.4270766 -1008.6015124
## 166 167 168 169 170
## 1515.2612392 -46.9702251 -306.2849543 83.6374155 2301.0035605
## 171 172 173 174 175
## 984.9823976 -0.5328199 -347.6496491 63.2388598 -358.8323973
## 176 177 178 179 180
## -331.9582465 950.8402101 -288.8575471 140.0493309 -1046.9404944
## 181 182 183 184 185
## 901.9237504 -361.5362838 -297.2474902 1038.6190193 3413.3636346
## 186 187 188 189 190
## -701.5982534 -290.6608357 4176.4555186 -246.7403241 997.3304134
## 191 192 193 194 195
## -264.4779717 737.0069572 -540.3215417 94.1097316 1243.7218600
## 196 197 198 199 200
## -189.1936960 537.0272519 -457.9205425 -356.0930494 132.8928336
## 201 202 203 204 205
## 958.8206287 177.5892801 -191.2734071 -123.5833956 1359.3356398
## 206 207 208 209 210
## -700.4884383 -421.9228766 -182.8332488 1274.7984792 -288.3369150
## 211 212 213 214 215
## -90.6383189 -993.6199753 -103.8428757 -347.6496491 -527.4988134
## 216 217 218 219 220
## 56.3436316 -345.1589458 -192.1321687 -325.8263881 -342.6541697
## 221 222 223 224 225
## -281.4347697 -63.8830206 -382.9677333 -63.8830206 -205.9967533
## 226 227 228 229 230
## -391.0646425 1038.6190193 -387.8867658 1052.9469997 -87.3510468
## 231 232 233 234 235
## -297.2474902 1015.4258003 842.8736068 -355.3867586 -176.9533708
## 236 237 238 239 240
## -196.0949110 -425.6521992 -893.5145957 -893.5145957 702.6508447
## 241 242 243 244 245
## -476.0378010 -196.0949110 -337.3943295 -490.5519907 -657.3557767
## 246 247 248 249 250
## 535.7126903 -72.8182300 1026.7524306 996.1715572 1362.9971241
## 251 252 253 254 255
## -273.9878455 -135.3671662 -347.6496491 -484.2401465 -51.7681500
## 256 257 258 259 260
## 1193.5152205 -867.4009691 -1041.6583944 -46.9702251 702.6508447
## 261 262 263 264 265
## -683.6800272 -106.8805557 -123.5833956 -297.2474902 196.1268923
## 266 267 268 269 270
## -183.1505294 -527.4988134 -251.7499383 -90.6383189 702.6508447
## 271 272 273 274 275
## -1023.6723773 132.8928336 -325.8263881 -1147.2374098 -253.6256261
## 276 277 278 279 280
## -552.6461005 -189.1936960 -290.6608357 -538.7162950 -652.9863898
## 281 282 283 284 285
## -402.3082199 -396.4678727 1408.9168418 -94.6207131 47.2910296
## 286 287 288 289 290
## -161.4315868 -347.6496491 -189.1936960 -134.3072828 -123.5833956
## 291 292 293 294 295
## -504.0956822 -778.8238420 -645.8451468 47.2910296 -215.3041271
## 296 297 298 299 300
## -286.2524489 140.0493309 307.9641549 1038.6190193 -482.8157163
## 301 302 303 304 305
## -492.7249110 -549.8958861 -106.8805557 -586.5582202 -563.9129859
## 306 307 308 309 310
## -123.5833956 -1150.7014721 4178.1695186 -123.5833956 -72.5290835
## 311 312 313 314 315
## 1778.3051756 -229.2024688 -279.3817917 -494.4270766 413.0498841
## 316 317 318 319 320
## -338.0996718 -196.0949110 -254.9352314 -421.9228766 -455.8619061
## 321 322 323 324 325
## 1155.2792042 -69.4762298 -1131.8732871 -157.4222592 -476.0378010
## 326 327 328 329 330
## 172.7226034 -778.8238420 757.5361064 -673.7163970 1155.2792042
## 331 332 333 334 335
## -119.4775773 949.7986068 -374.0745124 -494.4270766 11.6067007
## 336 337 338 339 340
## -264.2879464 -269.7155892 388.8692195 -165.9947674 -51.7681500
## 341 342 343 344 345
## -860.1478288 737.0069572 -347.6496491 -347.6052324 816.9291039
## 346 347 348 349 350
## -1008.6015124 -476.0378010 1436.7810533 -41.8479625 -494.4270766
## 351 352 353 354 355
## -325.8263881 -292.8914659 -72.6957440 -297.2474902 1274.7984792
## 356 357 358 359 360
## -0.5328199 -1095.9726229 -30.8392858 -391.0646425 3067.6422182
## 361 362 363 364 365
## -541.7741173 -300.7917727 -68.8151071 -476.6929199 -250.9978527
## 366 367 368 369 370
## -224.3032226 1989.3975723 -452.5206528 -876.9973278 -290.6608357
## 371 372 373 374 375
## -123.5833956 -359.9441396 -356.0930494 -993.6199753 -90.6383189
## 376 377 378 379 380
## 1184.7101047 -485.4017426 -755.7978814 364.6239477 -46.9702251
## 381 382 383 384 385
## -123.5833956 -523.7162281 1292.4884495 -211.1532343 997.3304134
## 386 387 388 389 390
## -543.5375374 -1008.6015124 -223.0380325 -146.9321105 -368.7912058
## 391 392 393 394 395
## -33.7518107 2215.7938693 -283.4120212 -68.8151071 594.8925826
## 396 397 398 399 400
## -235.8842799 979.8386126 127.2967080 -485.4017426 -1147.2374098
## 401 402 403 404 405
## -251.7499383 -289.4862639 -1131.8732871 -504.2675150 -123.5833956
## 406 407 408 409 410
## -668.4965992 -254.2853674 3067.6422182 -296.0662810 1038.6190193
## 411 412 413 414
## -347.6496491 -261.9780658 -494.4270766 -347.6496491#normalidad de los residuos:
hist(residuos, breaks = 15, col = "#B0E2FF")
shapiro.test(residuos)##
## Shapiro-Wilk normality test
##
## data: residuos
## W = 0.81685, p-value < 2.2e-16Como tiene un valor p muy menor a cero, se rechaza la hipotesis nula
#Media cero
plot(residuos, col="#B0E2FF")
abline(h=0)
t.test(residuos, mu=0)##
## One Sample t-test
##
## data: residuos
## t = 2.2303e-16, df = 413, p-value = 1
## alternative hypothesis: true mean is not equal to 0
## 95 percent confidence interval:
## -72.12113 72.12113
## sample estimates:
## mean of x
## 8.1828e-15De acuerdo al gráfico y los resultados de la prueba, se evidencia que la media estadÃsticamente es casi 0.
#Supuesto de independencia
residuos[2:length(residuos)]## 2 3 4 5 6
## -369.5612019 177.5892801 177.5892801 -90.6383189 -289.4862639
## 7 8 9 10 11
## -257.5783717 -204.8767907 1193.5152205 -527.4988134 -654.8730357
## 12 13 14 15 16
## -347.6496491 -325.8263881 -132.7944954 127.2967080 345.9981608
## 17 18 19 20 21
## -46.9702251 -876.9973278 23.5266277 -552.6461005 -256.9377872
## 22 23 24 25 26
## -5.7587510 1274.7984792 -5.7587510 -239.2223042 -663.6686233
## 27 28 29 30 31
## -0.5328199 -424.9044153 -220.7941406 267.7655952 949.7986068
## 32 33 34 35 36
## -266.8117071 -519.1294314 -133.6803904 -277.1659038 1987.5596981
## 37 38 39 40 41
## -394.2364023 1274.7984792 413.0498841 -123.5833956 1038.6190193
## 42 43 44 45 46
## 997.3304134 -284.6710465 68.7135588 397.0775598 172.7226034
## 47 48 49 50 51
## 123.9942749 -191.9066222 1029.8897747 910.6284462 -235.8842799
## 52 53 54 55 56
## 1964.8261611 -697.0434042 -325.8263881 -123.5833956 -140.1569983
## 57 58 59 60 61
## -233.2924163 -778.8238420 910.6284462 -680.2691334 -389.4182003
## 62 63 64 65 66
## -41.8479625 -288.6392639 397.0775598 958.8206287 -301.7640523
## 67 68 69 70 71
## -391.0646425 -494.4270766 -308.7444009 177.5892801 -347.6496491
## 72 73 74 75 76
## -191.9066222 -276.8092153 1038.6190193 -421.9228766 1274.7984792
## 77 78 79 80 81
## -181.7645143 -290.6608357 -501.6815035 1359.3356398 397.0775598
## 82 83 84 85 86
## -289.7400999 -325.6303717 -37.6123741 47.2910296 -30.8392858
## 87 88 89 90 91
## 1408.9168418 997.3304134 -60.7952055 813.0422600 -993.6199753
## 92 93 94 95 96
## -63.8830206 -132.7944954 -110.0328035 -458.8250674 -494.4270766
## 97 98 99 100 101
## -347.6496491 -491.0497852 -123.5833956 -347.6496491 -69.4762298
## 102 103 104 105 106
## -1147.2374098 -391.0646425 -538.7162950 -85.4453566 -46.9702251
## 107 108 109 110 111
## -249.9137940 1274.7984792 -342.2613609 -297.2474902 -494.4270766
## 112 113 114 115 116
## -298.5144605 -224.1660325 -375.0651537 -405.6669422 584.2770559
## 117 118 119 120 121
## 1696.4820566 1155.2792042 -579.0871951 -123.5833956 -325.8263881
## 122 123 124 125 126
## -325.8263881 78.9581296 -1008.6015124 -5.7587510 -391.0646425
## 127 128 129 130 131
## -185.7720275 -0.5328199 -492.8125655 -319.4104930 -338.2304547
## 132 133 134 135 136
## -297.2474902 -251.7499383 -215.8970897 -316.7832625 996.1715572
## 137 138 139 140 141
## -90.6383189 -140.9169602 -758.1673511 -325.8263881 -123.5833956
## 142 143 144 145 146
## -657.3557767 425.9635496 -325.8263881 1274.7984792 267.7655952
## 147 148 149 150 151
## -1008.6015124 173.7854034 1282.2560206 -301.7529189 -294.5613999
## 152 153 154 155 156
## -396.4678727 1274.7984792 -457.8010071 997.3304134 1038.6190193
## 157 158 159 160 161
## -72.5290835 -183.1505294 -90.6383189 -183.1505294 -755.7978814
## 162 163 164 165 166
## -181.7645143 997.3304134 -494.4270766 -1008.6015124 1515.2612392
## 167 168 169 170 171
## -46.9702251 -306.2849543 83.6374155 2301.0035605 984.9823976
## 172 173 174 175 176
## -0.5328199 -347.6496491 63.2388598 -358.8323973 -331.9582465
## 177 178 179 180 181
## 950.8402101 -288.8575471 140.0493309 -1046.9404944 901.9237504
## 182 183 184 185 186
## -361.5362838 -297.2474902 1038.6190193 3413.3636346 -701.5982534
## 187 188 189 190 191
## -290.6608357 4176.4555186 -246.7403241 997.3304134 -264.4779717
## 192 193 194 195 196
## 737.0069572 -540.3215417 94.1097316 1243.7218600 -189.1936960
## 197 198 199 200 201
## 537.0272519 -457.9205425 -356.0930494 132.8928336 958.8206287
## 202 203 204 205 206
## 177.5892801 -191.2734071 -123.5833956 1359.3356398 -700.4884383
## 207 208 209 210 211
## -421.9228766 -182.8332488 1274.7984792 -288.3369150 -90.6383189
## 212 213 214 215 216
## -993.6199753 -103.8428757 -347.6496491 -527.4988134 56.3436316
## 217 218 219 220 221
## -345.1589458 -192.1321687 -325.8263881 -342.6541697 -281.4347697
## 222 223 224 225 226
## -63.8830206 -382.9677333 -63.8830206 -205.9967533 -391.0646425
## 227 228 229 230 231
## 1038.6190193 -387.8867658 1052.9469997 -87.3510468 -297.2474902
## 232 233 234 235 236
## 1015.4258003 842.8736068 -355.3867586 -176.9533708 -196.0949110
## 237 238 239 240 241
## -425.6521992 -893.5145957 -893.5145957 702.6508447 -476.0378010
## 242 243 244 245 246
## -196.0949110 -337.3943295 -490.5519907 -657.3557767 535.7126903
## 247 248 249 250 251
## -72.8182300 1026.7524306 996.1715572 1362.9971241 -273.9878455
## 252 253 254 255 256
## -135.3671662 -347.6496491 -484.2401465 -51.7681500 1193.5152205
## 257 258 259 260 261
## -867.4009691 -1041.6583944 -46.9702251 702.6508447 -683.6800272
## 262 263 264 265 266
## -106.8805557 -123.5833956 -297.2474902 196.1268923 -183.1505294
## 267 268 269 270 271
## -527.4988134 -251.7499383 -90.6383189 702.6508447 -1023.6723773
## 272 273 274 275 276
## 132.8928336 -325.8263881 -1147.2374098 -253.6256261 -552.6461005
## 277 278 279 280 281
## -189.1936960 -290.6608357 -538.7162950 -652.9863898 -402.3082199
## 282 283 284 285 286
## -396.4678727 1408.9168418 -94.6207131 47.2910296 -161.4315868
## 287 288 289 290 291
## -347.6496491 -189.1936960 -134.3072828 -123.5833956 -504.0956822
## 292 293 294 295 296
## -778.8238420 -645.8451468 47.2910296 -215.3041271 -286.2524489
## 297 298 299 300 301
## 140.0493309 307.9641549 1038.6190193 -482.8157163 -492.7249110
## 302 303 304 305 306
## -549.8958861 -106.8805557 -586.5582202 -563.9129859 -123.5833956
## 307 308 309 310 311
## -1150.7014721 4178.1695186 -123.5833956 -72.5290835 1778.3051756
## 312 313 314 315 316
## -229.2024688 -279.3817917 -494.4270766 413.0498841 -338.0996718
## 317 318 319 320 321
## -196.0949110 -254.9352314 -421.9228766 -455.8619061 1155.2792042
## 322 323 324 325 326
## -69.4762298 -1131.8732871 -157.4222592 -476.0378010 172.7226034
## 327 328 329 330 331
## -778.8238420 757.5361064 -673.7163970 1155.2792042 -119.4775773
## 332 333 334 335 336
## 949.7986068 -374.0745124 -494.4270766 11.6067007 -264.2879464
## 337 338 339 340 341
## -269.7155892 388.8692195 -165.9947674 -51.7681500 -860.1478288
## 342 343 344 345 346
## 737.0069572 -347.6496491 -347.6052324 816.9291039 -1008.6015124
## 347 348 349 350 351
## -476.0378010 1436.7810533 -41.8479625 -494.4270766 -325.8263881
## 352 353 354 355 356
## -292.8914659 -72.6957440 -297.2474902 1274.7984792 -0.5328199
## 357 358 359 360 361
## -1095.9726229 -30.8392858 -391.0646425 3067.6422182 -541.7741173
## 362 363 364 365 366
## -300.7917727 -68.8151071 -476.6929199 -250.9978527 -224.3032226
## 367 368 369 370 371
## 1989.3975723 -452.5206528 -876.9973278 -290.6608357 -123.5833956
## 372 373 374 375 376
## -359.9441396 -356.0930494 -993.6199753 -90.6383189 1184.7101047
## 377 378 379 380 381
## -485.4017426 -755.7978814 364.6239477 -46.9702251 -123.5833956
## 382 383 384 385 386
## -523.7162281 1292.4884495 -211.1532343 997.3304134 -543.5375374
## 387 388 389 390 391
## -1008.6015124 -223.0380325 -146.9321105 -368.7912058 -33.7518107
## 392 393 394 395 396
## 2215.7938693 -283.4120212 -68.8151071 594.8925826 -235.8842799
## 397 398 399 400 401
## 979.8386126 127.2967080 -485.4017426 -1147.2374098 -251.7499383
## 402 403 404 405 406
## -289.4862639 -1131.8732871 -504.2675150 -123.5833956 -668.4965992
## 407 408 409 410 411
## -254.2853674 3067.6422182 -296.0662810 1038.6190193 -347.6496491
## 412 413 414
## -261.9780658 -494.4270766 -347.6496491residuos[1:length(residuos)-1]## 1 2 3 4 5
## -542.8713322 -369.5612019 177.5892801 177.5892801 -90.6383189
## 6 7 8 9 10
## -289.4862639 -257.5783717 -204.8767907 1193.5152205 -527.4988134
## 11 12 13 14 15
## -654.8730357 -347.6496491 -325.8263881 -132.7944954 127.2967080
## 16 17 18 19 20
## 345.9981608 -46.9702251 -876.9973278 23.5266277 -552.6461005
## 21 22 23 24 25
## -256.9377872 -5.7587510 1274.7984792 -5.7587510 -239.2223042
## 26 27 28 29 30
## -663.6686233 -0.5328199 -424.9044153 -220.7941406 267.7655952
## 31 32 33 34 35
## 949.7986068 -266.8117071 -519.1294314 -133.6803904 -277.1659038
## 36 37 38 39 40
## 1987.5596981 -394.2364023 1274.7984792 413.0498841 -123.5833956
## 41 42 43 44 45
## 1038.6190193 997.3304134 -284.6710465 68.7135588 397.0775598
## 46 47 48 49 50
## 172.7226034 123.9942749 -191.9066222 1029.8897747 910.6284462
## 51 52 53 54 55
## -235.8842799 1964.8261611 -697.0434042 -325.8263881 -123.5833956
## 56 57 58 59 60
## -140.1569983 -233.2924163 -778.8238420 910.6284462 -680.2691334
## 61 62 63 64 65
## -389.4182003 -41.8479625 -288.6392639 397.0775598 958.8206287
## 66 67 68 69 70
## -301.7640523 -391.0646425 -494.4270766 -308.7444009 177.5892801
## 71 72 73 74 75
## -347.6496491 -191.9066222 -276.8092153 1038.6190193 -421.9228766
## 76 77 78 79 80
## 1274.7984792 -181.7645143 -290.6608357 -501.6815035 1359.3356398
## 81 82 83 84 85
## 397.0775598 -289.7400999 -325.6303717 -37.6123741 47.2910296
## 86 87 88 89 90
## -30.8392858 1408.9168418 997.3304134 -60.7952055 813.0422600
## 91 92 93 94 95
## -993.6199753 -63.8830206 -132.7944954 -110.0328035 -458.8250674
## 96 97 98 99 100
## -494.4270766 -347.6496491 -491.0497852 -123.5833956 -347.6496491
## 101 102 103 104 105
## -69.4762298 -1147.2374098 -391.0646425 -538.7162950 -85.4453566
## 106 107 108 109 110
## -46.9702251 -249.9137940 1274.7984792 -342.2613609 -297.2474902
## 111 112 113 114 115
## -494.4270766 -298.5144605 -224.1660325 -375.0651537 -405.6669422
## 116 117 118 119 120
## 584.2770559 1696.4820566 1155.2792042 -579.0871951 -123.5833956
## 121 122 123 124 125
## -325.8263881 -325.8263881 78.9581296 -1008.6015124 -5.7587510
## 126 127 128 129 130
## -391.0646425 -185.7720275 -0.5328199 -492.8125655 -319.4104930
## 131 132 133 134 135
## -338.2304547 -297.2474902 -251.7499383 -215.8970897 -316.7832625
## 136 137 138 139 140
## 996.1715572 -90.6383189 -140.9169602 -758.1673511 -325.8263881
## 141 142 143 144 145
## -123.5833956 -657.3557767 425.9635496 -325.8263881 1274.7984792
## 146 147 148 149 150
## 267.7655952 -1008.6015124 173.7854034 1282.2560206 -301.7529189
## 151 152 153 154 155
## -294.5613999 -396.4678727 1274.7984792 -457.8010071 997.3304134
## 156 157 158 159 160
## 1038.6190193 -72.5290835 -183.1505294 -90.6383189 -183.1505294
## 161 162 163 164 165
## -755.7978814 -181.7645143 997.3304134 -494.4270766 -1008.6015124
## 166 167 168 169 170
## 1515.2612392 -46.9702251 -306.2849543 83.6374155 2301.0035605
## 171 172 173 174 175
## 984.9823976 -0.5328199 -347.6496491 63.2388598 -358.8323973
## 176 177 178 179 180
## -331.9582465 950.8402101 -288.8575471 140.0493309 -1046.9404944
## 181 182 183 184 185
## 901.9237504 -361.5362838 -297.2474902 1038.6190193 3413.3636346
## 186 187 188 189 190
## -701.5982534 -290.6608357 4176.4555186 -246.7403241 997.3304134
## 191 192 193 194 195
## -264.4779717 737.0069572 -540.3215417 94.1097316 1243.7218600
## 196 197 198 199 200
## -189.1936960 537.0272519 -457.9205425 -356.0930494 132.8928336
## 201 202 203 204 205
## 958.8206287 177.5892801 -191.2734071 -123.5833956 1359.3356398
## 206 207 208 209 210
## -700.4884383 -421.9228766 -182.8332488 1274.7984792 -288.3369150
## 211 212 213 214 215
## -90.6383189 -993.6199753 -103.8428757 -347.6496491 -527.4988134
## 216 217 218 219 220
## 56.3436316 -345.1589458 -192.1321687 -325.8263881 -342.6541697
## 221 222 223 224 225
## -281.4347697 -63.8830206 -382.9677333 -63.8830206 -205.9967533
## 226 227 228 229 230
## -391.0646425 1038.6190193 -387.8867658 1052.9469997 -87.3510468
## 231 232 233 234 235
## -297.2474902 1015.4258003 842.8736068 -355.3867586 -176.9533708
## 236 237 238 239 240
## -196.0949110 -425.6521992 -893.5145957 -893.5145957 702.6508447
## 241 242 243 244 245
## -476.0378010 -196.0949110 -337.3943295 -490.5519907 -657.3557767
## 246 247 248 249 250
## 535.7126903 -72.8182300 1026.7524306 996.1715572 1362.9971241
## 251 252 253 254 255
## -273.9878455 -135.3671662 -347.6496491 -484.2401465 -51.7681500
## 256 257 258 259 260
## 1193.5152205 -867.4009691 -1041.6583944 -46.9702251 702.6508447
## 261 262 263 264 265
## -683.6800272 -106.8805557 -123.5833956 -297.2474902 196.1268923
## 266 267 268 269 270
## -183.1505294 -527.4988134 -251.7499383 -90.6383189 702.6508447
## 271 272 273 274 275
## -1023.6723773 132.8928336 -325.8263881 -1147.2374098 -253.6256261
## 276 277 278 279 280
## -552.6461005 -189.1936960 -290.6608357 -538.7162950 -652.9863898
## 281 282 283 284 285
## -402.3082199 -396.4678727 1408.9168418 -94.6207131 47.2910296
## 286 287 288 289 290
## -161.4315868 -347.6496491 -189.1936960 -134.3072828 -123.5833956
## 291 292 293 294 295
## -504.0956822 -778.8238420 -645.8451468 47.2910296 -215.3041271
## 296 297 298 299 300
## -286.2524489 140.0493309 307.9641549 1038.6190193 -482.8157163
## 301 302 303 304 305
## -492.7249110 -549.8958861 -106.8805557 -586.5582202 -563.9129859
## 306 307 308 309 310
## -123.5833956 -1150.7014721 4178.1695186 -123.5833956 -72.5290835
## 311 312 313 314 315
## 1778.3051756 -229.2024688 -279.3817917 -494.4270766 413.0498841
## 316 317 318 319 320
## -338.0996718 -196.0949110 -254.9352314 -421.9228766 -455.8619061
## 321 322 323 324 325
## 1155.2792042 -69.4762298 -1131.8732871 -157.4222592 -476.0378010
## 326 327 328 329 330
## 172.7226034 -778.8238420 757.5361064 -673.7163970 1155.2792042
## 331 332 333 334 335
## -119.4775773 949.7986068 -374.0745124 -494.4270766 11.6067007
## 336 337 338 339 340
## -264.2879464 -269.7155892 388.8692195 -165.9947674 -51.7681500
## 341 342 343 344 345
## -860.1478288 737.0069572 -347.6496491 -347.6052324 816.9291039
## 346 347 348 349 350
## -1008.6015124 -476.0378010 1436.7810533 -41.8479625 -494.4270766
## 351 352 353 354 355
## -325.8263881 -292.8914659 -72.6957440 -297.2474902 1274.7984792
## 356 357 358 359 360
## -0.5328199 -1095.9726229 -30.8392858 -391.0646425 3067.6422182
## 361 362 363 364 365
## -541.7741173 -300.7917727 -68.8151071 -476.6929199 -250.9978527
## 366 367 368 369 370
## -224.3032226 1989.3975723 -452.5206528 -876.9973278 -290.6608357
## 371 372 373 374 375
## -123.5833956 -359.9441396 -356.0930494 -993.6199753 -90.6383189
## 376 377 378 379 380
## 1184.7101047 -485.4017426 -755.7978814 364.6239477 -46.9702251
## 381 382 383 384 385
## -123.5833956 -523.7162281 1292.4884495 -211.1532343 997.3304134
## 386 387 388 389 390
## -543.5375374 -1008.6015124 -223.0380325 -146.9321105 -368.7912058
## 391 392 393 394 395
## -33.7518107 2215.7938693 -283.4120212 -68.8151071 594.8925826
## 396 397 398 399 400
## -235.8842799 979.8386126 127.2967080 -485.4017426 -1147.2374098
## 401 402 403 404 405
## -251.7499383 -289.4862639 -1131.8732871 -504.2675150 -123.5833956
## 406 407 408 409 410
## -668.4965992 -254.2853674 3067.6422182 -296.0662810 1038.6190193
## 411 412 413
## -347.6496491 -261.9780658 -494.4270766plot(residuos[1:length(residuos)-1],residuos[2:length(residuos)], xlab = "Residuos resagados", ylab = "Residuos")
#prueba de durbin
#install.packages("lmtest")
library(lmtest)## Loading required package: zoo##
## Attaching package: 'zoo'## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
dwtest(modelo, alternative = "two.sided")##
## Durbin-Watson test
##
## data: modelo
## DW = 2.1249, p-value = 0.2027
## alternative hypothesis: true autocorrelation is not 0``` En este caso, de acuerdo al valor-p se deduce que los erros si son independientes,es decir, no se rechaza la hipotesis nula.
#varianza Homogenea
plot(residuos, col="#B0E2FF")
abline(h=0)
bptest(modelo)##
## studentized Breusch-Pagan test
##
## data: modelo
## BP = 6.3039, df = 1, p-value = 0.01205Segun los resultados no hay homogeneas
En conclusion, no todos los supuestos se cumplieron, por ende, no seria factible modelarlo con modelo lineal simple