1 Wprowadzenie

Cel: wyznaczenie obszaru ufności dla dystrybuanty nieznanego rozkładu, a nie tylko oszacowania parametrów, od jakich zależą jej wartości.

  • Brzegi tego obszaru są wykresami funkcji „przedziałami stałych” (funkcji schodkowych).

  • Jeżeli przy wyznaczaniu pasma ufności dla dystrybuanty otrzymamy lewy kraniec przedziału będący liczbą ujemną, to zastępujemy ją przez zero.

  • Jeżeli otrzymamy prawy kraniec przedziału większy od jedności, to przyjmujemy, że jest on równy jeden.

  • Określenie obszaru ufności dla dystrybuanty w przedstawiony sposób polega na wyznaczeniu przedziałowego oszacowania dla każdej wartości dystrybuanty.

1.1 Funkcja CDF

Funkcja w programie R odpowiedzialna za estymację to np. CDF z pakietu spatstat. CDF jest metodą ogólną, z metodą dla klasy “gęstość”.

Oblicza ona skumulowaną funkcję rozkładu, której gęstość prawdopodobieństwa została oszacowana i zapisana w obiekcie f. Obiekt f musi należeć do klasy “gęstość” i zazwyczaj zostałby uzyskany z wywołania funkcji gęstość.

1.2 Funkcja kde

Pakiet R o nazwie snpar zawiera kilka uzupełniających metod statystyki nieparametrycznej, w tym test kwantylowy, test trendu Coxa-Stuarta, test przebiegów, test normalnego wyniku, estymację jądra PDF i CDF, estymację regresji jądra i test jądra Kołmogorowa-Smirnowa.

Funkcja kde zawiera obliczanie zarówno nieparametrycznego estymatora jądra funkcji gęstości prawdopodobieństwa (PDF) jak i funkcji rozkładu skumulowanego (CDF).

1.3 Przykład 1.

   b <- density(runif(10))
   f <- CDF(b)
   f(0.5)
## [1] 0.474115
   plot(f)

1.4 Przykład 2.

x <- rnorm(200,2,3)
# with default bandwidth
kde(x, kernel = "quar", plot = TRUE)

## $data
##   [1]  1.36704130  8.54906064  6.77237754  4.13231281  1.16924510  8.58741587
##   [7] -0.69039644  5.06757034  3.21957353 -1.21156088 -6.03668687  3.11024914
##  [13] -1.82283676  0.78024130  1.81307506  3.93442450 -3.61453974 -0.17908949
##  [19]  5.64409476 -1.46413734  9.01226147  1.50482466  3.39620404  6.31051112
##  [25]  1.68083673  9.12104191  2.36107062  5.21561924  7.63368619  0.77823868
##  [31] -0.20772370  0.83542761  4.23378307  2.68643673  7.40517582  0.93763970
##  [37] -2.03414773  1.48208995 -0.30644004  2.77885762  2.52003069  2.34947169
##  [43] -5.17851223  5.13648787  4.46516247  2.23721650  2.30961562  4.47976792
##  [49] -1.64419658 -0.30143556  2.08078780 -2.79003465  3.89479230 -0.73196973
##  [55]  1.32810791  5.79462210  1.49021346  2.13839950  3.14027651  5.44891445
##  [61] -1.03174300  1.89905304  3.79740207  2.59718039  1.82225654 -4.80565835
##  [67]  2.46274169  5.28836331  2.12304914  6.71334984  1.93563254  0.33338843
##  [73] -0.61743287  3.41635507  0.82052570  1.84856020 -0.81803113 -3.91465980
##  [79]  8.12370209  4.59515337  4.54541217  4.94130311  0.67727637  2.45761181
##  [85] -1.83581014 -0.74427453  4.95639853 -2.39138367  2.71449483 -2.60534810
##  [91] -0.49021905 -1.24395597  1.39088864  4.91986737  4.36494067  2.04433727
##  [97] -2.88615615  1.23269378  6.44145383  4.72410573  9.27861265  0.52070851
## [103]  2.99448126  7.08986454  6.10315237  3.69506635  3.41884977  2.22363216
## [109] -1.47497083 -1.24938589  3.62446584  2.69286981  2.40610564  3.64637881
## [115] -0.51279143  0.03831646  1.67168773  6.44233093  0.77373944  1.83631679
## [121]  3.73053718  2.28811820  2.16036138 -5.83403584  1.05517069 -1.01096773
## [127]  1.73014913  1.70491123  2.42338293 -1.93911012  2.14721538  5.28590444
## [133]  0.83998426 -1.68217049  4.12511893  1.57721270 -3.84229922 -0.05899220
## [139]  1.02833886  8.04594971  1.00396181  4.90334585 -3.33732952  5.83243806
## [145] -2.72371342  8.65556876 -0.64216814 -2.00486320  0.68118820 -0.81616619
## [151] -3.27924236 -4.56834998  2.22718972  4.95815667  5.82823206  3.66761315
## [157]  2.25434821  2.40832642  3.16049605  2.26275820  0.59026123  4.04067893
## [163]  4.13142004  0.60174949  5.40342579 -4.53817836  4.43786870  1.02213977
## [169]  0.87873889  1.20655753  2.32981234  2.65966172 -0.37172963 -1.00367999
## [175]  1.61360376 -0.81052096  3.70973528  2.66679753  0.70006873  5.40631273
## [181]  6.52842321  0.04009414  1.55339718  4.31340605  1.09441621  6.04083676
## [187]  1.30451219  3.06082455 -1.78749668  2.39208423 -0.30559266  1.92098328
## [193]  3.05895469 -0.39124351  1.31245943  0.84744788  3.22111788  1.80381694
## [199] -2.86405044  0.39775469
## 
## $xgrid
##   [1]  1.36704130  8.54906064  6.77237754  4.13231281  1.16924510  8.58741587
##   [7] -0.69039644  5.06757034  3.21957353 -1.21156088 -6.03668687  3.11024914
##  [13] -1.82283676  0.78024130  1.81307506  3.93442450 -3.61453974 -0.17908949
##  [19]  5.64409476 -1.46413734  9.01226147  1.50482466  3.39620404  6.31051112
##  [25]  1.68083673  9.12104191  2.36107062  5.21561924  7.63368619  0.77823868
##  [31] -0.20772370  0.83542761  4.23378307  2.68643673  7.40517582  0.93763970
##  [37] -2.03414773  1.48208995 -0.30644004  2.77885762  2.52003069  2.34947169
##  [43] -5.17851223  5.13648787  4.46516247  2.23721650  2.30961562  4.47976792
##  [49] -1.64419658 -0.30143556  2.08078780 -2.79003465  3.89479230 -0.73196973
##  [55]  1.32810791  5.79462210  1.49021346  2.13839950  3.14027651  5.44891445
##  [61] -1.03174300  1.89905304  3.79740207  2.59718039  1.82225654 -4.80565835
##  [67]  2.46274169  5.28836331  2.12304914  6.71334984  1.93563254  0.33338843
##  [73] -0.61743287  3.41635507  0.82052570  1.84856020 -0.81803113 -3.91465980
##  [79]  8.12370209  4.59515337  4.54541217  4.94130311  0.67727637  2.45761181
##  [85] -1.83581014 -0.74427453  4.95639853 -2.39138367  2.71449483 -2.60534810
##  [91] -0.49021905 -1.24395597  1.39088864  4.91986737  4.36494067  2.04433727
##  [97] -2.88615615  1.23269378  6.44145383  4.72410573  9.27861265  0.52070851
## [103]  2.99448126  7.08986454  6.10315237  3.69506635  3.41884977  2.22363216
## [109] -1.47497083 -1.24938589  3.62446584  2.69286981  2.40610564  3.64637881
## [115] -0.51279143  0.03831646  1.67168773  6.44233093  0.77373944  1.83631679
## [121]  3.73053718  2.28811820  2.16036138 -5.83403584  1.05517069 -1.01096773
## [127]  1.73014913  1.70491123  2.42338293 -1.93911012  2.14721538  5.28590444
## [133]  0.83998426 -1.68217049  4.12511893  1.57721270 -3.84229922 -0.05899220
## [139]  1.02833886  8.04594971  1.00396181  4.90334585 -3.33732952  5.83243806
## [145] -2.72371342  8.65556876 -0.64216814 -2.00486320  0.68118820 -0.81616619
## [151] -3.27924236 -4.56834998  2.22718972  4.95815667  5.82823206  3.66761315
## [157]  2.25434821  2.40832642  3.16049605  2.26275820  0.59026123  4.04067893
## [163]  4.13142004  0.60174949  5.40342579 -4.53817836  4.43786870  1.02213977
## [169]  0.87873889  1.20655753  2.32981234  2.65966172 -0.37172963 -1.00367999
## [175]  1.61360376 -0.81052096  3.70973528  2.66679753  0.70006873  5.40631273
## [181]  6.52842321  0.04009414  1.55339718  4.31340605  1.09441621  6.04083676
## [187]  1.30451219  3.06082455 -1.78749668  2.39208423 -0.30559266  1.92098328
## [193]  3.05895469 -0.39124351  1.31245943  0.84744788  3.22111788  1.80381694
## [199] -2.86405044  0.39775469
## 
## $fhat
##   [1] 0.140070156 0.019482861 0.035102083 0.088824578 0.135160426 0.019249238
##   [7] 0.080010614 0.072375506 0.115277200 0.069432731 0.008038720 0.118844954
##  [13] 0.057782584 0.122881864 0.146110963 0.093656274 0.025851914 0.092306584
##  [19] 0.060097585 0.064899586 0.016423912 0.142735230 0.109588598 0.044505539
##  [25] 0.145145235 0.015554409 0.141270143 0.069429620 0.025021341 0.122811689
##  [31] 0.091571832 0.124784812 0.086544493 0.132529944 0.026725001 0.128166007
##  [37] 0.052959722 0.142340825 0.089079363 0.129579036 0.137391465 0.141517684
##  [43] 0.013685354 0.071031328 0.082133347 0.143619071 0.142326470 0.081893110
##  [49] 0.061523937 0.089203546 0.145583315 0.036821276 0.094697842 0.079095760
##  [55] 0.139199123 0.056541973 0.142483750 0.144998867 0.117867074 0.064519624
##  [61] 0.072899384 0.146317221 0.097372440 0.135229540 0.146149066 0.016089003
##  [67] 0.138888243 0.067933334 0.145170925 0.036170394 0.146300147 0.106901987
##  [73] 0.081662979 0.108944701 0.124277118 0.146238116 0.077249668 0.022805247
##  [79] 0.022014890 0.080089556 0.080848199 0.074656390 0.119198293 0.139017079
##  [85] 0.057498477 0.078828707 0.074396916 0.044596602 0.131642977 0.040164671
##  [91] 0.084635104 0.068836726 0.140578774 0.075018918 0.083892101 0.145863704
##  [97] 0.035258652 0.136859004 0.041595095 0.078159938 0.014175117 0.113483956
## [103] 0.122593150 0.030050260 0.049298915 0.100318324 0.108865077 0.143836492
## [109] 0.064705813 0.068737165 0.102438594 0.132327778 0.140260416 0.101773183
## [115] 0.084100705 0.097980514 0.145051137 0.041576100 0.122653760 0.146200486
## [121] 0.099282233 0.142734231 0.144732937 0.009343142 0.131857384 0.073313155
## [127] 0.145593848 0.145376564 0.139853675 0.055177589 0.144894822 0.067984157
## [133] 0.124939194 0.060759437 0.088990699 0.143871659 0.023467066 0.095409075
## [139] 0.131036493 0.022456152 0.130278261 0.075294373 0.029112483 0.055640029
## [145] 0.037970911 0.018834512 0.081096928 0.053649360 0.119340280 0.077289037
## [151] 0.029835720 0.017832910 0.143780366 0.074366452 0.055740095 0.101134316
## [157] 0.143333292 0.140208728 0.117206972 0.143188634 0.116019746 0.090989375
## [163] 0.088845159 0.116440578 0.065508163 0.018062529 0.082591894 0.130844729
## [169] 0.126238536 0.136170417 0.141924808 0.133361549 0.087475531 0.073458660
## [175] 0.144370122 0.077408417 0.099887500 0.133141628 0.120023821 0.065445852
## [181] 0.039758163 0.098028419 0.143518812 0.084883825 0.133029520 0.050755990
## [187] 0.138647089 0.120447352 0.058549323 0.140582692 0.089100376 0.146313988
## [193] 0.120507889 0.087002802 0.138835027 0.125191365 0.115226947 0.146068735
## [199] 0.035606733 0.109117088
## 
## $Fhat
##   [1] 0.417969342 0.976529611 0.931073530 0.764639808 0.390730422 0.977272404
##   [7] 0.194300105 0.839659310 0.672188105 0.155432935 0.006183447 0.659390383
##  [13] 0.116423972 0.340451767 0.482078991 0.746593993 0.045601599 0.238282707
##  [19] 0.877955881 0.138473143 0.984875018 0.437459929 0.692046119 0.912783466
##  [25] 0.462812964 0.986615076 0.561486301 0.850158983 0.956196411 0.340205752
##  [31] 0.235650106 0.347285956 0.773536182 0.606114314 0.950292348 0.360214717
##  [37] 0.104716527 0.434219335 0.226734181 0.618227046 0.583645795 0.559846277
##  [43] 0.015489979 0.844601275 0.793026621 0.543837134 0.554189604 0.794224457
##  [49] 0.127085688 0.227180287 0.521201794 0.071144489 0.742861638 0.190992890
##  [55] 0.412532730 0.886736055 0.435376224 0.529573064 0.662944312 0.865790685
##  [61] 0.168225606 0.494652680 0.733509920 0.594163147 0.483420684 0.021032112
##  [67] 0.575731411 0.855155260 0.527345944 0.928970146 0.500004756 0.289137593
##  [73] 0.200197919 0.694247952 0.345430200 0.487266178 0.184265623 0.038318316
##  [79] 0.967698183 0.803568189 0.799565677 0.830374014 0.327987776 0.575018601
##  [85] 0.115676177 0.190021277 0.831499030 0.087303308 0.609820440 0.078246852
##  [91] 0.210774644 0.153193318 0.421315745 0.828769802 0.784708632 0.515889877
##  [97] 0.067681319 0.399360548 0.918419126 0.813771944 0.988958803 0.309772686
## [103] 0.645414824 0.941377842 0.903059821 0.723395642 0.694519637 0.541884677
## [109] 0.137771103 0.152819811 0.716238684 0.606966240 0.567825947 0.718476118
## [115] 0.208870267 0.258963125 0.461485458 0.918455600 0.339653547 0.485475948
## [121] 0.726935584 0.551125532 0.532754633 0.007943980 0.375497427 0.169744407
## [127] 0.469981890 0.466310095 0.570245767 0.109855569 0.530850900 0.854988158
## [133] 0.347854908 0.124763835 0.764000217 0.447834517 0.039992115 0.249554512
## [139] 0.371970431 0.965969215 0.368785368 0.827528097 0.053213909 0.888857179
## [145] 0.073624360 0.978570142 0.198184973 0.106277536 0.328454337 0.184409725
## [151] 0.054925931 0.025054770 0.542396285 0.831629804 0.888622946 0.720630410
## [157] 0.546295144 0.568137377 0.665320858 0.547499968 0.317753808 0.756402041
## [163] 0.764560499 0.319089091 0.862833241 0.025596278 0.790778668 0.371158718
## [169] 0.352722140 0.395792528 0.557060104 0.602554652 0.220970746 0.170279224
## [175] 0.453079384 0.184846377 0.724864040 0.603505511 0.330714004 0.863022270
## [181] 0.921956074 0.259137346 0.444412298 0.780360032 0.380695354 0.899942344
## [187] 0.409254705 0.653476893 0.118479593 0.565857030 0.226809674 0.497861452
## [193] 0.653251616 0.219268377 0.410357314 0.348788349 0.672366095 0.480726472
## [199] 0.068464573 0.296089379
## 
## $bw
## [1] 2.225777
# with specified bandwidth
kde(x, h = 4, kernel = "quar", plot = TRUE)

## $data
##   [1]  1.36704130  8.54906064  6.77237754  4.13231281  1.16924510  8.58741587
##   [7] -0.69039644  5.06757034  3.21957353 -1.21156088 -6.03668687  3.11024914
##  [13] -1.82283676  0.78024130  1.81307506  3.93442450 -3.61453974 -0.17908949
##  [19]  5.64409476 -1.46413734  9.01226147  1.50482466  3.39620404  6.31051112
##  [25]  1.68083673  9.12104191  2.36107062  5.21561924  7.63368619  0.77823868
##  [31] -0.20772370  0.83542761  4.23378307  2.68643673  7.40517582  0.93763970
##  [37] -2.03414773  1.48208995 -0.30644004  2.77885762  2.52003069  2.34947169
##  [43] -5.17851223  5.13648787  4.46516247  2.23721650  2.30961562  4.47976792
##  [49] -1.64419658 -0.30143556  2.08078780 -2.79003465  3.89479230 -0.73196973
##  [55]  1.32810791  5.79462210  1.49021346  2.13839950  3.14027651  5.44891445
##  [61] -1.03174300  1.89905304  3.79740207  2.59718039  1.82225654 -4.80565835
##  [67]  2.46274169  5.28836331  2.12304914  6.71334984  1.93563254  0.33338843
##  [73] -0.61743287  3.41635507  0.82052570  1.84856020 -0.81803113 -3.91465980
##  [79]  8.12370209  4.59515337  4.54541217  4.94130311  0.67727637  2.45761181
##  [85] -1.83581014 -0.74427453  4.95639853 -2.39138367  2.71449483 -2.60534810
##  [91] -0.49021905 -1.24395597  1.39088864  4.91986737  4.36494067  2.04433727
##  [97] -2.88615615  1.23269378  6.44145383  4.72410573  9.27861265  0.52070851
## [103]  2.99448126  7.08986454  6.10315237  3.69506635  3.41884977  2.22363216
## [109] -1.47497083 -1.24938589  3.62446584  2.69286981  2.40610564  3.64637881
## [115] -0.51279143  0.03831646  1.67168773  6.44233093  0.77373944  1.83631679
## [121]  3.73053718  2.28811820  2.16036138 -5.83403584  1.05517069 -1.01096773
## [127]  1.73014913  1.70491123  2.42338293 -1.93911012  2.14721538  5.28590444
## [133]  0.83998426 -1.68217049  4.12511893  1.57721270 -3.84229922 -0.05899220
## [139]  1.02833886  8.04594971  1.00396181  4.90334585 -3.33732952  5.83243806
## [145] -2.72371342  8.65556876 -0.64216814 -2.00486320  0.68118820 -0.81616619
## [151] -3.27924236 -4.56834998  2.22718972  4.95815667  5.82823206  3.66761315
## [157]  2.25434821  2.40832642  3.16049605  2.26275820  0.59026123  4.04067893
## [163]  4.13142004  0.60174949  5.40342579 -4.53817836  4.43786870  1.02213977
## [169]  0.87873889  1.20655753  2.32981234  2.65966172 -0.37172963 -1.00367999
## [175]  1.61360376 -0.81052096  3.70973528  2.66679753  0.70006873  5.40631273
## [181]  6.52842321  0.04009414  1.55339718  4.31340605  1.09441621  6.04083676
## [187]  1.30451219  3.06082455 -1.78749668  2.39208423 -0.30559266  1.92098328
## [193]  3.05895469 -0.39124351  1.31245943  0.84744788  3.22111788  1.80381694
## [199] -2.86405044  0.39775469
## 
## $xgrid
##   [1]  1.36704130  8.54906064  6.77237754  4.13231281  1.16924510  8.58741587
##   [7] -0.69039644  5.06757034  3.21957353 -1.21156088 -6.03668687  3.11024914
##  [13] -1.82283676  0.78024130  1.81307506  3.93442450 -3.61453974 -0.17908949
##  [19]  5.64409476 -1.46413734  9.01226147  1.50482466  3.39620404  6.31051112
##  [25]  1.68083673  9.12104191  2.36107062  5.21561924  7.63368619  0.77823868
##  [31] -0.20772370  0.83542761  4.23378307  2.68643673  7.40517582  0.93763970
##  [37] -2.03414773  1.48208995 -0.30644004  2.77885762  2.52003069  2.34947169
##  [43] -5.17851223  5.13648787  4.46516247  2.23721650  2.30961562  4.47976792
##  [49] -1.64419658 -0.30143556  2.08078780 -2.79003465  3.89479230 -0.73196973
##  [55]  1.32810791  5.79462210  1.49021346  2.13839950  3.14027651  5.44891445
##  [61] -1.03174300  1.89905304  3.79740207  2.59718039  1.82225654 -4.80565835
##  [67]  2.46274169  5.28836331  2.12304914  6.71334984  1.93563254  0.33338843
##  [73] -0.61743287  3.41635507  0.82052570  1.84856020 -0.81803113 -3.91465980
##  [79]  8.12370209  4.59515337  4.54541217  4.94130311  0.67727637  2.45761181
##  [85] -1.83581014 -0.74427453  4.95639853 -2.39138367  2.71449483 -2.60534810
##  [91] -0.49021905 -1.24395597  1.39088864  4.91986737  4.36494067  2.04433727
##  [97] -2.88615615  1.23269378  6.44145383  4.72410573  9.27861265  0.52070851
## [103]  2.99448126  7.08986454  6.10315237  3.69506635  3.41884977  2.22363216
## [109] -1.47497083 -1.24938589  3.62446584  2.69286981  2.40610564  3.64637881
## [115] -0.51279143  0.03831646  1.67168773  6.44233093  0.77373944  1.83631679
## [121]  3.73053718  2.28811820  2.16036138 -5.83403584  1.05517069 -1.01096773
## [127]  1.73014913  1.70491123  2.42338293 -1.93911012  2.14721538  5.28590444
## [133]  0.83998426 -1.68217049  4.12511893  1.57721270 -3.84229922 -0.05899220
## [139]  1.02833886  8.04594971  1.00396181  4.90334585 -3.33732952  5.83243806
## [145] -2.72371342  8.65556876 -0.64216814 -2.00486320  0.68118820 -0.81616619
## [151] -3.27924236 -4.56834998  2.22718972  4.95815667  5.82823206  3.66761315
## [157]  2.25434821  2.40832642  3.16049605  2.26275820  0.59026123  4.04067893
## [163]  4.13142004  0.60174949  5.40342579 -4.53817836  4.43786870  1.02213977
## [169]  0.87873889  1.20655753  2.32981234  2.65966172 -0.37172963 -1.00367999
## [175]  1.61360376 -0.81052096  3.70973528  2.66679753  0.70006873  5.40631273
## [181]  6.52842321  0.04009414  1.55339718  4.31340605  1.09441621  6.04083676
## [187]  1.30451219  3.06082455 -1.78749668  2.39208423 -0.30559266  1.92098328
## [193]  3.05895469 -0.39124351  1.31245943  0.84744788  3.22111788  1.80381694
## [199] -2.86405044  0.39775469
## 
## $fhat
##   [1] 0.120213962 0.019407731 0.041405061 0.094229021 0.118623541 0.019046369
##   [7] 0.084466799 0.072159800 0.111880592 0.071837670 0.009123518 0.113453998
##  [13] 0.058563579 0.114157253 0.122002622 0.098686091 0.030399125 0.096471461
##  [19] 0.059936964 0.066055604 0.015389102 0.121032743 0.109086408 0.048318401
##  [25] 0.121736258 0.014556543 0.120857160 0.068850590 0.029535442 0.114129610
##  [31] 0.095833096 0.114900005 0.091850034 0.118406920 0.032503455 0.116175477
##  [37] 0.054466973 0.120913663 0.093599964 0.117488508 0.119817744 0.120920226
##  [43] 0.014520791 0.070607808 0.086309274 0.121440786 0.121123723 0.085956930
##  [49] 0.062192198 0.093714341 0.121898322 0.041705131 0.099542516 0.083452862
##  [55] 0.119939440 0.057075666 0.120956934 0.121764026 0.113032787 0.063861211
##  [61] 0.076153686 0.122059437 0.101588417 0.119203975 0.122012793 0.017458842
##  [67] 0.120228283 0.067262043 0.121803643 0.042271671 0.122058135 0.106946221
##  [73] 0.086240453 0.108746668 0.114703097 0.122036313 0.081352406 0.026596775
##  [79] 0.023754242 0.083176970 0.084373838 0.075043266 0.112675864 0.120263167
##  [85] 0.058306142 0.083152559 0.074695966 0.048087593 0.118137697 0.044571293
##  [91] 0.089302605 0.071074755 0.120372679 0.075537425 0.088721794 0.121962467
##  [97] 0.040271167 0.119186788 0.046320287 0.080103188 0.013413715 0.110210486
## [103] 0.114993124 0.036823963 0.051641918 0.103643819 0.108704316 0.121492602
## [109] 0.065816399 0.070947460 0.105005389 0.118345968 0.120595321 0.104587533
## [115] 0.088762925 0.101155539 0.121709477 0.046307051 0.114067330 0.122026357
## [121] 0.102942661 0.121225024 0.121702572 0.010238171 0.117491688 0.076657401
## [127] 0.121862050 0.121801589 0.120487734 0.056284459 0.121740032 0.067315283
## [133] 0.114959667 0.061405989 0.094395780 0.121369595 0.027491729 0.099096578
## [139] 0.117204430 0.024618296 0.116936586 0.075919085 0.034033861 0.056380099
## [145] 0.042717486 0.018415124 0.085640337 0.055022308 0.112734323 0.081397919
## [151] 0.034804224 0.019551954 0.121479268 0.074655554 0.056457015 0.104178478
## [157] 0.121371968 0.120581713 0.112744500 0.121336772 0.111335188 0.096328208
## [163] 0.094249731 0.111516418 0.064810048 0.019835206 0.086967439 0.117136932
## [169] 0.115456588 0.118960753 0.121023156 0.118655605 0.092095098 0.076834203
## [175] 0.121514251 0.081535703 0.103355362 0.118590121 0.113014121 0.064749475
## [181] 0.045013122 0.101192527 0.121265938 0.089955987 0.117897511 0.052693223
## [187] 0.119763894 0.114128378 0.059268736 0.120679734 0.093619340 0.122060478
## [193] 0.114153399 0.091640555 0.119823785 0.115056833 0.111857544 0.121991302
## [199] 0.040597470 0.108106927
## 
## $Fhat
##   [1] 0.42986526 0.97076785 0.91816350 0.74580968 0.40623665 0.97150530
##   [7] 0.21291292 0.82354618 0.65116281 0.17219670 0.01087393 0.63884452
##  [13] 0.13246448 0.36090381 0.48397707 0.72671716 0.05474949 0.25922033
##  [19] 0.86153546 0.15479040 0.97879562 0.44648785 0.67068235 0.89745705
##  [25] 0.46785876 0.98042405 0.55068674 0.83398325 0.94858568 0.36067523
##  [31] 0.25646707 0.36722440 0.75525082 0.58964528 0.94150060 0.37903487
##  [37] 0.12052575 0.44373755 0.24711661 0.60054681 0.56981978 0.54928456
##  [43] 0.02088773 0.82846568 0.77586405 0.53567989 0.54446103 0.77712206
##  [49] 0.14324787 0.24758531 0.51664341 0.08435429 0.72278900 0.20942243
##  [55] 0.42519021 0.87034045 0.44471997 0.52366250 0.64224494 0.84945783
##  [61] 0.18550089 0.49446965 0.71299420 0.57904046 0.48509728 0.02683810
##  [67] 0.56294359 0.83893378 0.52179307 0.91569388 0.49893455 0.31142900
##  [73] 0.21914069 0.67287714 0.36551363 0.48830699 0.20233074 0.04620205
##  [79] 0.96161111 0.78687974 0.78271267 0.81425325 0.34922485 0.56232675
##  [85] 0.13170638 0.20839740 0.81538344 0.10222813 0.59296380 0.09231905
##  [91] 0.23030691 0.16988189 0.43273395 0.81263935 0.76709298 0.51219893
##  [97] 0.08041476 0.41378129 0.90365260 0.79740688 0.98262672 0.33177330
## [103] 0.62561973 0.93057637 0.88709748 0.70249207 0.67314838 0.53402984
## [109] 0.15407608 0.16949630 0.69512644 0.59040680 0.55612375 0.69742285
## [115] 0.22829722 0.28070848 0.46674512 0.90369322 0.36016187 0.48681291
## [121] 0.70615600 0.54185609 0.52633600 0.01283462 0.39276790 0.18708823
## [127] 0.47386510 0.47079030 0.55820639 0.12578819 0.52473585 0.83876833
## [133] 0.36774809 0.14090114 0.74513121 0.45526176 0.04815887 0.27096482
## [139] 0.38961922 0.95973073 0.38676537 0.81138821 0.06367869 0.87248564
## [145] 0.08715369 0.97278177 0.21701492 0.12212891 0.34966573 0.20248250
## [151] 0.06567797 0.03122511 0.53446204 0.81551473 0.87224835 0.69963936
## [157] 0.53775980 0.55639155 0.64452751 0.53878038 0.33947813 0.73707850
## [163] 0.74572554 0.34075822 0.84653134 0.03181928 0.77349936 0.38889287
## [169] 0.37221300 0.41066913 0.54690633 0.58647158 0.24105450 0.18764753
## [175] 0.45968121 0.20294240 0.70401030 0.58731806 0.35179686 0.84671835
## [181] 0.90762413 0.28088833 0.45237250 0.76248891 0.39738694 0.88384676
## [187] 0.42236221 0.63322034 0.13454657 0.55443224 0.24719593 0.49714647
## [193] 0.63300691 0.23926180 0.42331424 0.36860647 0.65133558 0.48284760
## [199] 0.08130859 0.31835029
## 
## $bw
## [1] 4

1.5 Przeczytaj

Przeczytaj artykuł naukowy “Kernel-smoothed cumulative distribution function estimation with akdensity” autorstwa Philippe Van Kerm.

1.6 Zadanie

Posłużymy się zbiorem danych diagnozy społecznej.

Na jego podstawie Twoim zadaniem jest oszacowanie rozkładu “p64 Pana/Pani wlasny (osobisty) dochod miesieczny netto (na reke)” według województw/płci.

Postaraj się oszacować zarówno rozkład gęstości jak i skumulowanej gęstości (dystrybuanty).

data("diagnoza")
data("diagnozaDict")

diagnoza_filtered <- diagnoza %>%
  select(gp64, wojewodztwo, plec) %>% 
  filter(!is.na(gp64))

diagnoza_filtered$gp64 <- as.numeric(diagnoza_filtered$gp64)

summary(diagnoza_filtered)
##       gp64              wojewodztwo          plec      
##  Min.   :  100   Mazowieckie  :2489   mężczyzna: 8918  
##  1st Qu.: 1000   Śląskie      :1941   kobieta  :10770  
##  Median : 1500   Wielkopolskie:1534                    
##  Mean   : 1739   Łódzkie      :1449                    
##  3rd Qu.: 2000   Lubelskie    :1415                    
##  Max.   :50000   Dolnośląskie :1381                    
##                  (Other)      :9479
ggplot(diagnoza_filtered, aes(x = gp64, color = plec)) +
  geom_density() +
  facet_wrap(~ wojewodztwo) +
  labs(title = "Estymacja gęstości dochodu netto według województw i płci",
       x = "Dochód netto (na rękę)",
       y = "Gęstość")

sample_data <- diagnoza_filtered %>% filter(wojewodztwo == "MAZOWIECKIE", plec == "Mężczyzna")

if (nrow(sample_data) > 2) {
  density_estimation <- density(sample_data$gp64, kernel = "gaussian")
  cumulative_estimation <- CDF(density_estimation)
  
  # Wizualizacja funkcji skumulowanej dystrybuanty (CDF) dla przykładowych danych
  plot(cumulative_estimation, main = "Skumulowana dystrybuanta dochodu netto\nMazowieckie - Mężczyźni", 
       xlab = "Dochód netto (na rękę)", ylab = "CDF")
  
  # Obliczenie przykładowej wartości dystrybuanty dla dochodu netto na poziomie 2000 PLN
  cumulative_estimation(2000)
} else {
  cat("Niewystarczająca liczba danych do estymacji rozkładu gęstości.\n")
}
## Niewystarczająca liczba danych do estymacji rozkładu gęstości.

#Odpowiedź do zadania: Estymacja rozkładu gęstości (PDF): Wykres pokazuje, jak rozkładają się dochody netto w zależności od województwa i płci. Dzięki temu widać, jak dochody różnią się między regionami i pomiędzy kobietami a mężczyznami. Na przykład można zobaczyć, które województwa mają wyższe lub niższe dochody i jakie są różnice między płciami.

Estymacja skumulowanej funkcji rozkładu (CDF): Wykres CDF dla przykładowego województwa (Mazowieckie) i płci (Mężczyźni) pokazuje prawdopodobieństwo, że losowa osoba z tej grupy zarabia określoną kwotę lub mniej.

Znaczenie funkcji CDF: CDF pomaga w analizach dochodów, ponieważ pozwala oszacować, jaka część osób mieści się w danym przedziale dochodowym. To przydatne przy badaniu nierówności dochodowych lub ustalaniu progów do różnych świadczeń społecznych.

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