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] 0.5168977
   plot(f)

1.4 Przykład 2.

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

## $data
##   [1] -0.42154591 -1.71741500  2.32944312  6.95420179  3.72320587  0.13637644
##   [7]  8.18323582  6.67360861 -3.62063700  5.16722486 -1.44969589 -5.81235773
##  [13] -0.93238794  3.23495267  0.57002601  4.02778905  1.21465821  3.93768648
##  [19]  0.72593458  6.16857731  4.72234300  6.06184101 -5.23697941  3.59967230
##  [25]  0.08212184 -0.56954923  1.55502767 -0.55224652  1.84085570  1.37669268
##  [31]  5.62119118  3.75473651  1.35283832  4.04954525 -0.86965973 -0.07529414
##  [37]  2.27608736  0.48593941  1.13100555  3.92202327  4.38273137  3.22755815
##  [43]  1.10340123  1.92621372 -0.37592250  3.99459123 -0.02182100  0.23288304
##  [49]  4.85150105  1.96319852  1.61512440  4.06290297  5.35493786 -0.88658410
##  [55]  1.80296443 -1.49372211 -0.36522687  4.64817306  1.43566339  0.63205881
##  [61]  3.03731284  7.10304544  1.09974324  4.48447515  1.43667919 -0.42902393
##  [67]  2.74699792 -4.43237314  1.54290660  1.73744290 -2.47065180  1.27599620
##  [73]  7.46985480 -3.50238211  3.46852300  0.38682716  2.90579295  5.58244542
##  [79]  1.37400305  0.64422915 -2.38772283  2.31661454  0.87004146 -2.51778650
##  [85]  3.53726947 -0.57297461  5.78975459 -2.13971413  3.21783277  1.78776838
##  [91]  4.96604416  3.38008857  4.03822252  5.84581619  1.50124232 -0.43477560
##  [97]  1.74321048  4.17139330 -0.36361542 -0.63743003  8.36087652  3.17339124
## [103]  0.09191296  1.32405944  2.39036161 -3.67629356  4.17166229 -3.52634749
## [109] -0.96119364  3.37084380  1.64766048  1.99954471  2.15588168  6.12160444
## [115] -3.10436718  2.66492043  0.93537295 -2.98483964  0.85183737  0.48846283
## [121]  3.09124090  1.02021847  3.92585390 -0.34783687  4.09786090  3.65209140
## [127]  0.22886827 -2.76065596  0.31145121  3.11039463  1.44779989  0.18298156
## [133] -1.44030384  1.44055317 -0.47912963  5.80311506  3.91034983  3.97426744
## [139]  4.88179695  8.28372894  5.25345369  5.08185990  2.47912856  2.13575473
## [145]  2.19113563  4.92334530  2.67980301  0.63835665 -1.88613461  4.61367503
## [151]  1.29629751 -0.25539714 -0.62943299  1.38487986  4.01327952  2.05187628
## [157]  1.81629860  8.53468601  3.20692175  5.68536038  4.65451508  9.16490148
## [163]  4.60854086  0.52403666  1.30069294 -3.30953398  1.02618864 -1.61703546
## [169]  4.41749569  3.65032153  4.16457468 -2.40534642 -3.73358752  3.15162312
## [175]  3.55917790  0.64103082 -5.87481674  0.51386478  6.98467599  3.10504831
## [181]  1.32695241  4.24511932 -0.07341424  1.75215998 -0.50443920 -0.29041501
## [187]  0.13431450  0.57431302  2.24530802 -1.94959655  7.17005524  2.92845723
## [193]  1.34160397  0.83538541  7.68399871  1.34569758  4.14075170  1.79188826
## [199]  3.37080357  5.58434842
## 
## $xgrid
##   [1] -0.42154591 -1.71741500  2.32944312  6.95420179  3.72320587  0.13637644
##   [7]  8.18323582  6.67360861 -3.62063700  5.16722486 -1.44969589 -5.81235773
##  [13] -0.93238794  3.23495267  0.57002601  4.02778905  1.21465821  3.93768648
##  [19]  0.72593458  6.16857731  4.72234300  6.06184101 -5.23697941  3.59967230
##  [25]  0.08212184 -0.56954923  1.55502767 -0.55224652  1.84085570  1.37669268
##  [31]  5.62119118  3.75473651  1.35283832  4.04954525 -0.86965973 -0.07529414
##  [37]  2.27608736  0.48593941  1.13100555  3.92202327  4.38273137  3.22755815
##  [43]  1.10340123  1.92621372 -0.37592250  3.99459123 -0.02182100  0.23288304
##  [49]  4.85150105  1.96319852  1.61512440  4.06290297  5.35493786 -0.88658410
##  [55]  1.80296443 -1.49372211 -0.36522687  4.64817306  1.43566339  0.63205881
##  [61]  3.03731284  7.10304544  1.09974324  4.48447515  1.43667919 -0.42902393
##  [67]  2.74699792 -4.43237314  1.54290660  1.73744290 -2.47065180  1.27599620
##  [73]  7.46985480 -3.50238211  3.46852300  0.38682716  2.90579295  5.58244542
##  [79]  1.37400305  0.64422915 -2.38772283  2.31661454  0.87004146 -2.51778650
##  [85]  3.53726947 -0.57297461  5.78975459 -2.13971413  3.21783277  1.78776838
##  [91]  4.96604416  3.38008857  4.03822252  5.84581619  1.50124232 -0.43477560
##  [97]  1.74321048  4.17139330 -0.36361542 -0.63743003  8.36087652  3.17339124
## [103]  0.09191296  1.32405944  2.39036161 -3.67629356  4.17166229 -3.52634749
## [109] -0.96119364  3.37084380  1.64766048  1.99954471  2.15588168  6.12160444
## [115] -3.10436718  2.66492043  0.93537295 -2.98483964  0.85183737  0.48846283
## [121]  3.09124090  1.02021847  3.92585390 -0.34783687  4.09786090  3.65209140
## [127]  0.22886827 -2.76065596  0.31145121  3.11039463  1.44779989  0.18298156
## [133] -1.44030384  1.44055317 -0.47912963  5.80311506  3.91034983  3.97426744
## [139]  4.88179695  8.28372894  5.25345369  5.08185990  2.47912856  2.13575473
## [145]  2.19113563  4.92334530  2.67980301  0.63835665 -1.88613461  4.61367503
## [151]  1.29629751 -0.25539714 -0.62943299  1.38487986  4.01327952  2.05187628
## [157]  1.81629860  8.53468601  3.20692175  5.68536038  4.65451508  9.16490148
## [163]  4.60854086  0.52403666  1.30069294 -3.30953398  1.02618864 -1.61703546
## [169]  4.41749569  3.65032153  4.16457468 -2.40534642 -3.73358752  3.15162312
## [175]  3.55917790  0.64103082 -5.87481674  0.51386478  6.98467599  3.10504831
## [181]  1.32695241  4.24511932 -0.07341424  1.75215998 -0.50443920 -0.29041501
## [187]  0.13431450  0.57431302  2.24530802 -1.94959655  7.17005524  2.92845723
## [193]  1.34160397  0.83538541  7.68399871  1.34569758  4.14075170  1.79188826
## [199]  3.37080357  5.58434842
## 
## $fhat
##   [1] 0.097300927 0.051423210 0.125530822 0.030011461 0.111568977 0.121223971
##   [7] 0.018728215 0.033789926 0.025853912 0.075431476 0.059019984 0.006960251
##  [13] 0.077224485 0.115269296 0.135387558 0.108530821 0.139925715 0.109582701
##  [19] 0.138490767 0.042948137 0.092426659 0.045493926 0.009652045 0.112461370
##  [25] 0.119065260 0.091074719 0.136650618 0.091790530 0.132822374 0.138647054
##  [31] 0.058857958 0.111317293 0.138876775 0.108247748 0.079514924 0.112478275
##  [37] 0.126251994 0.133222359 0.140345285 0.109749531 0.102275492 0.115337170
##  [43] 0.140441613 0.131485270 0.099257279 0.108939515 0.114762108 0.124909059
##  [49] 0.087725977 0.130896260 0.135923132 0.108067946 0.068332965 0.078898400
##  [55] 0.133391035 0.057635839 0.099719323 0.094919563 0.138029676 0.136770399
##  [61] 0.117205567 0.028257534 0.140452792 0.099753736 0.138018530 0.096982280
##  [67] 0.120271509 0.016398304 0.136794833 0.134331365 0.037719068 0.139516692
##  [73] 0.024478045 0.027378042 0.113321610 0.130255841 0.118582831 0.060191010
##  [79] 0.138673615 0.137019470 0.038709782 0.125703094 0.140137491 0.037230032
##  [85] 0.112864960 0.090933438 0.053331953 0.042505440 0.115427031 0.133613602
##  [91] 0.083321114 0.114010267 0.108396597 0.051602966 0.137283984 0.096737516
##  [97] 0.134250929 0.106439444 0.099789092 0.088312371 0.017274989 0.115846643
## [103] 0.119459547 0.139134425 0.124718068 0.025143343 0.106435009 0.027067814
## [109] 0.076169998 0.114087095 0.135518467 0.130314730 0.127949250 0.044025890
## [115] 0.032107318 0.121197803 0.140479116 0.033281795 0.139998293 0.133292033
## [121] 0.116657827 0.140599186 0.109709139 0.100474487 0.107576501 0.112100690
## [127] 0.124759839 0.035218133 0.127737182 0.116465764 0.137895571 0.123028060
## [133] 0.059321648 0.137975889 0.094855394 0.052914724 0.109871276 0.109176536
## [139] 0.086579689 0.017920048 0.072119081 0.078766157 0.123528545 0.128240966
## [145] 0.127442530 0.084984148 0.121026094 0.136900217 0.047425182 0.096016993
## [151] 0.139362242 0.104552611 0.088633154 0.138565215 0.108712737 0.129494060
## [157] 0.133193537 0.015667642 0.115528580 0.056697703 0.094713587 0.009470852
## [163] 0.096176888 0.134242875 0.139327466 0.029814830 0.140595774 0.054055533
## [169] 0.101453969 0.112113355 0.106551193 0.038484878 0.024413760 0.116058195
## [175] 0.112725406 0.136954737 0.006786960 0.133976765 0.029635238 0.116519139
## [181] 0.139109517 0.105141958 0.112559351 0.134125070 0.093787659 0.102999082
## [187] 0.121143103 0.135489087 0.126675905 0.046075272 0.027522104 0.118342206
## [193] 0.138979959 0.139855213 0.022533537 0.138942745 0.106931301 0.133553508
## [199] 0.114087431 0.060125113
## 
## $Fhat
##   [1] 0.203067417 0.108767938 0.558579552 0.950437495 0.722628687 0.264127821
##   [7] 0.979748812 0.941503663 0.038669539 0.864284518 0.123510048 0.006678591
##  [13] 0.158656100 0.667296302 0.320012837 0.756184373 0.409854275 0.746356762
##  [19] 0.341379030 0.922265929 0.826881217 0.917549047 0.011345482 0.708789558
##  [25] 0.257609136 0.189129824 0.456984932 0.190711851 0.495520768 0.432432168
##  [31] 0.894689349 0.726142595 0.429122065 0.758542534 0.163572172 0.239379264
##  [37] 0.551862580 0.308717344 0.398130270 0.744639033 0.793704889 0.666443691
##  [43] 0.394254755 0.506801441 0.207551167 0.752574528 0.245455106 0.276006135
##  [49] 0.838519156 0.511653520 0.465175408 0.759987282 0.877771310 0.162231648
##  [55] 0.490477113 0.120942277 0.208615256 0.819932373 0.440590388 0.328455162
##  [61] 0.644326730 0.954771371 0.393741001 0.803985548 0.440730592 0.202340990
##  [67] 0.609858238 0.021662533 0.455327705 0.481706032 0.075842789 0.418424917
##  [73] 0.964424901 0.041816777 0.693984469 0.295656859 0.628821974 0.892383089
##  [79] 0.432059223 0.330121228 0.079010691 0.556968065 0.361470065 0.074076648
##  [85] 0.701758958 0.188818100 0.904138159 0.089060072 0.665321556 0.488448402
##  [91] 0.848317043 0.683933291 0.757316028 0.907079309 0.449618029 0.201783884
##  [97] 0.482480567 0.771626068 0.208776005 0.183041848 0.982948262 0.660182543
## [103] 0.258776850 0.425121586 0.566201916 0.037250382 0.771654698 0.041164369
## [109] 0.156446786 0.682878938 0.469591264 0.516400530 0.536585347 0.920223477
## [115] 0.053693436 0.599948981 0.370637946 0.057602105 0.358920226 0.309053608
## [121] 0.650632613 0.382564389 0.745059365 0.210355934 0.763756609 0.714675361
## [127] 0.275504952 0.065288388 0.285932330 0.652865202 0.442264773 0.269819685
## [133] 0.124065781 0.441265191 0.197534964 0.904847909 0.743357165 0.750358039
## [139] 0.841159570 0.981590435 0.870645494 0.857703180 0.577220050 0.534007187
## [145] 0.541087119 0.844723752 0.601751437 0.329316930 0.100436983 0.816638792
## [151] 0.421255737 0.219831643 0.183749367 0.433566963 0.754608315 0.523198507
## [157] 0.492254457 0.985814053 0.664061577 0.898396575 0.820533702 0.993697178
## [163] 0.816145413 0.313812396 0.421868218 0.047334116 0.383403780 0.114060122
## [169] 0.797246264 0.714476946 0.770899916 0.078330478 0.035830750 0.657658483
## [175] 0.704230122 0.329683098 0.006249295 0.312448244 0.951346323 0.652242397
## [181] 0.425524062 0.779426605 0.239590788 0.483681484 0.195147739 0.216197647
## [187] 0.263877948 0.320593462 0.547970126 0.097470619 0.956640148 0.631506841
## [193] 0.427561292 0.356618134 0.969454797 0.428130145 0.768356990 0.488998749
## [199] 0.682874348 0.892497570
## 
## $bw
## [1] 2.174173
# with specified bandwidth
kde(x, h = 4, kernel = "quar", plot = TRUE)

## $data
##   [1] -0.42154591 -1.71741500  2.32944312  6.95420179  3.72320587  0.13637644
##   [7]  8.18323582  6.67360861 -3.62063700  5.16722486 -1.44969589 -5.81235773
##  [13] -0.93238794  3.23495267  0.57002601  4.02778905  1.21465821  3.93768648
##  [19]  0.72593458  6.16857731  4.72234300  6.06184101 -5.23697941  3.59967230
##  [25]  0.08212184 -0.56954923  1.55502767 -0.55224652  1.84085570  1.37669268
##  [31]  5.62119118  3.75473651  1.35283832  4.04954525 -0.86965973 -0.07529414
##  [37]  2.27608736  0.48593941  1.13100555  3.92202327  4.38273137  3.22755815
##  [43]  1.10340123  1.92621372 -0.37592250  3.99459123 -0.02182100  0.23288304
##  [49]  4.85150105  1.96319852  1.61512440  4.06290297  5.35493786 -0.88658410
##  [55]  1.80296443 -1.49372211 -0.36522687  4.64817306  1.43566339  0.63205881
##  [61]  3.03731284  7.10304544  1.09974324  4.48447515  1.43667919 -0.42902393
##  [67]  2.74699792 -4.43237314  1.54290660  1.73744290 -2.47065180  1.27599620
##  [73]  7.46985480 -3.50238211  3.46852300  0.38682716  2.90579295  5.58244542
##  [79]  1.37400305  0.64422915 -2.38772283  2.31661454  0.87004146 -2.51778650
##  [85]  3.53726947 -0.57297461  5.78975459 -2.13971413  3.21783277  1.78776838
##  [91]  4.96604416  3.38008857  4.03822252  5.84581619  1.50124232 -0.43477560
##  [97]  1.74321048  4.17139330 -0.36361542 -0.63743003  8.36087652  3.17339124
## [103]  0.09191296  1.32405944  2.39036161 -3.67629356  4.17166229 -3.52634749
## [109] -0.96119364  3.37084380  1.64766048  1.99954471  2.15588168  6.12160444
## [115] -3.10436718  2.66492043  0.93537295 -2.98483964  0.85183737  0.48846283
## [121]  3.09124090  1.02021847  3.92585390 -0.34783687  4.09786090  3.65209140
## [127]  0.22886827 -2.76065596  0.31145121  3.11039463  1.44779989  0.18298156
## [133] -1.44030384  1.44055317 -0.47912963  5.80311506  3.91034983  3.97426744
## [139]  4.88179695  8.28372894  5.25345369  5.08185990  2.47912856  2.13575473
## [145]  2.19113563  4.92334530  2.67980301  0.63835665 -1.88613461  4.61367503
## [151]  1.29629751 -0.25539714 -0.62943299  1.38487986  4.01327952  2.05187628
## [157]  1.81629860  8.53468601  3.20692175  5.68536038  4.65451508  9.16490148
## [163]  4.60854086  0.52403666  1.30069294 -3.30953398  1.02618864 -1.61703546
## [169]  4.41749569  3.65032153  4.16457468 -2.40534642 -3.73358752  3.15162312
## [175]  3.55917790  0.64103082 -5.87481674  0.51386478  6.98467599  3.10504831
## [181]  1.32695241  4.24511932 -0.07341424  1.75215998 -0.50443920 -0.29041501
## [187]  0.13431450  0.57431302  2.24530802 -1.94959655  7.17005524  2.92845723
## [193]  1.34160397  0.83538541  7.68399871  1.34569758  4.14075170  1.79188826
## [199]  3.37080357  5.58434842
## 
## $xgrid
##   [1] -0.42154591 -1.71741500  2.32944312  6.95420179  3.72320587  0.13637644
##   [7]  8.18323582  6.67360861 -3.62063700  5.16722486 -1.44969589 -5.81235773
##  [13] -0.93238794  3.23495267  0.57002601  4.02778905  1.21465821  3.93768648
##  [19]  0.72593458  6.16857731  4.72234300  6.06184101 -5.23697941  3.59967230
##  [25]  0.08212184 -0.56954923  1.55502767 -0.55224652  1.84085570  1.37669268
##  [31]  5.62119118  3.75473651  1.35283832  4.04954525 -0.86965973 -0.07529414
##  [37]  2.27608736  0.48593941  1.13100555  3.92202327  4.38273137  3.22755815
##  [43]  1.10340123  1.92621372 -0.37592250  3.99459123 -0.02182100  0.23288304
##  [49]  4.85150105  1.96319852  1.61512440  4.06290297  5.35493786 -0.88658410
##  [55]  1.80296443 -1.49372211 -0.36522687  4.64817306  1.43566339  0.63205881
##  [61]  3.03731284  7.10304544  1.09974324  4.48447515  1.43667919 -0.42902393
##  [67]  2.74699792 -4.43237314  1.54290660  1.73744290 -2.47065180  1.27599620
##  [73]  7.46985480 -3.50238211  3.46852300  0.38682716  2.90579295  5.58244542
##  [79]  1.37400305  0.64422915 -2.38772283  2.31661454  0.87004146 -2.51778650
##  [85]  3.53726947 -0.57297461  5.78975459 -2.13971413  3.21783277  1.78776838
##  [91]  4.96604416  3.38008857  4.03822252  5.84581619  1.50124232 -0.43477560
##  [97]  1.74321048  4.17139330 -0.36361542 -0.63743003  8.36087652  3.17339124
## [103]  0.09191296  1.32405944  2.39036161 -3.67629356  4.17166229 -3.52634749
## [109] -0.96119364  3.37084380  1.64766048  1.99954471  2.15588168  6.12160444
## [115] -3.10436718  2.66492043  0.93537295 -2.98483964  0.85183737  0.48846283
## [121]  3.09124090  1.02021847  3.92585390 -0.34783687  4.09786090  3.65209140
## [127]  0.22886827 -2.76065596  0.31145121  3.11039463  1.44779989  0.18298156
## [133] -1.44030384  1.44055317 -0.47912963  5.80311506  3.91034983  3.97426744
## [139]  4.88179695  8.28372894  5.25345369  5.08185990  2.47912856  2.13575473
## [145]  2.19113563  4.92334530  2.67980301  0.63835665 -1.88613461  4.61367503
## [151]  1.29629751 -0.25539714 -0.62943299  1.38487986  4.01327952  2.05187628
## [157]  1.81629860  8.53468601  3.20692175  5.68536038  4.65451508  9.16490148
## [163]  4.60854086  0.52403666  1.30069294 -3.30953398  1.02618864 -1.61703546
## [169]  4.41749569  3.65032153  4.16457468 -2.40534642 -3.73358752  3.15162312
## [175]  3.55917790  0.64103082 -5.87481674  0.51386478  6.98467599  3.10504831
## [181]  1.32695241  4.24511932 -0.07341424  1.75215998 -0.50443920 -0.29041501
## [187]  0.13431450  0.57431302  2.24530802 -1.94959655  7.17005524  2.92845723
## [193]  1.34160397  0.83538541  7.68399871  1.34569758  4.14075170  1.79188826
## [199]  3.37080357  5.58434842
## 
## $fhat
##   [1] 0.094774871 0.062741888 0.123501447 0.037257978 0.104569216 0.105976129
##   [7] 0.019547975 0.042703382 0.027077073 0.073726357 0.069646029 0.008937085
##  [13] 0.082889182 0.113119064 0.113471347 0.098484396 0.121600963 0.100335411
##  [19] 0.115816608 0.053044599 0.083431763 0.055249183 0.012643079 0.106869070
##  [25] 0.104973156 0.091465548 0.123975213 0.091858717 0.124746646 0.122915040
##  [31] 0.064307008 0.103964853 0.122742286 0.098031869 0.084417949 0.101976089
##  [37] 0.123790573 0.112114970 0.120797891 0.100653061 0.090886041 0.113237737
##  [43] 0.120514856 0.124759684 0.095768802 0.099170943 0.103011530 0.107729847
##  [49] 0.080588857 0.124735085 0.124233658 0.097753107 0.069781933 0.084007619
##  [55] 0.124710158 0.068499151 0.095999895 0.085062845 0.123311537 0.114430442
##  [61] 0.116144431 0.034558514 0.120476690 0.088654636 0.123317980 0.094610695
##  [67] 0.119926138 0.018694675 0.123916801 0.124600626 0.045485432 0.122136885
##  [73] 0.028549163 0.028597619 0.109203292 0.110445336 0.117970874 0.065103288
##  [79] 0.122895914 0.114614462 0.047162373 0.123574390 0.117783836 0.044560272
##  [85] 0.107991878 0.091387531 0.060849382 0.052522839 0.113393243 0.124690153
##  [91] 0.078078254 0.110721760 0.098267622 0.059700646 0.123700097 0.094484187
##  [97] 0.124612707 0.095463934 0.096034648 0.089909107 0.017768650 0.114095201
## [103] 0.105155137 0.122524291 0.123125668 0.026387029 0.095458199 0.028283922
## [109] 0.082179465 0.110877957 0.124352113 0.124692955 0.124307661 0.054014347
## [115] 0.034339802 0.120815725 0.118606547 0.036263282 0.117546851 0.112156543
## [121] 0.115351112 0.119608852 0.100575493 0.096374004 0.097020530 0.105906773
## [127] 0.107657562 0.040087631 0.109131235 0.115063300 0.123387656 0.106827209
## [133] 0.069890921 0.123342432 0.093502200 0.060575882 0.100889042 0.099588647
## [139] 0.079923713 0.018527830 0.071895943 0.075561225 0.122489912 0.124375858
## [145] 0.124175229 0.079012539 0.120660881 0.114525835 0.058524995 0.085819847
## [151] 0.122304044 0.098330826 0.090093603 0.122972703 0.098785079 0.124600975
## [157] 0.124725155 0.016144965 0.113566914 0.062988837 0.084923601 0.011158789
## [163] 0.085932527 0.112737142 0.122339560 0.031246323 0.119676524 0.065306259
## [169] 0.090124085 0.105939578 0.095609216 0.046800807 0.025695330 0.114433517
## [175] 0.107600260 0.114566232 0.008576475 0.112572217 0.036692569 0.115143940
## [181] 0.122546683 0.093882357 0.102012822 0.124630521 0.092936640 0.097596024
## [187] 0.105938255 0.113538801 0.123940586 0.056978599 0.033395910 0.117668366
## [193] 0.122658448 0.117329759 0.025458614 0.122689185 0.096115270 0.124695890
## [199] 0.110878636 0.065064174
## 
## $Fhat
##   [1] 0.23173124 0.12909218 0.54963287 0.93861058 0.71068859 0.28783041
##   [7] 0.97243899 0.92740122 0.04765667 0.83979395 0.14680920 0.01058723
##  [13] 0.18629728 0.65748771 0.33545230 0.74162484 0.41144918 0.73266746
##  [19] 0.35332909 0.90323448 0.80484625 0.89745507 0.01676139 0.69762759
##  [25] 0.28210786 0.21794761 0.45328444 0.21953361 0.48885777 0.43126362
##  [31] 0.87111128 0.71397621 0.42833361 0.74376257 0.19154484 0.26581733
##  [37] 0.54303548 0.32596748 0.40130996 0.73109340 0.77524538 0.65665081
##  [43] 0.39797930 0.49950714 0.23607792 0.73834396 0.27129809 0.29814270
##  [49] 0.81543846 0.50412096 0.46074296 0.74507019 0.85326084 0.19011959
##  [55] 0.48413159 0.14376820 0.23710346 0.79859760 0.43852392 0.34252118
##  [61] 0.63482665 0.94395331 0.39753853 0.78437898 0.43864918 0.23102312
##  [67] 0.60053708 0.02931830 0.45178208 0.47596365 0.08860228 0.41892461
##  [73] 0.95550127 0.05094788 0.68345765 0.31493768 0.61942944 0.86860423
##  [79] 0.43093305 0.34391496 0.09244344 0.54804805 0.37016328 0.08648023
##  [85] 0.69092350 0.21763444 0.88165944 0.10479448 0.65554877 0.48223664
##  [91] 0.82452545 0.67373285 0.74265124 0.88503857 0.44662360 0.23047932
##  [97] 0.47668233 0.75555170 0.23725819 0.21179156 0.97575183 0.65049375
## [103] 0.28313656 0.42480433 0.55714519 0.04616894 0.75557738 0.05026629
## [109] 0.18391981 0.67270853 0.46478701 0.50865389 0.52812221 0.90072005
## [115] 0.06343789 0.59065675 0.37788539 0.06765655 0.36802128 0.32625044
## [121] 0.64106882 0.38799167 0.73147881 0.23877615 0.74847464 0.70320443
## [127] 0.29771033 0.07620964 0.30666206 0.64327547 0.44002095 0.29278930
## [133] 0.14746446 0.43912696 0.22631030 0.88247059 0.72991705 0.73632419
## [139] 0.81786990 0.97435189 0.84607216 0.83342211 0.56804724 0.52561958
## [145] 0.53250226 0.82117166 0.59245365 0.34324215 0.11886399 0.79565004
## [151] 0.42140586 0.24777581 0.21251130 0.43227019 0.74019370 0.51517702
## [157] 0.48579460 0.97869738 0.65431059 0.87519551 0.79913663 0.98723563
## [163] 0.79520914 0.33025064 0.42194351 0.05671447 0.38870596 0.13551857
## [169] 0.77839173 0.70301696 0.75490027 0.09161546 0.04467703 0.64800642
## [175] 0.69328515 0.34354846 0.01004034 0.32910473 0.93973735 0.64266009
## [181] 0.42515883 0.76253169 0.26600907 0.47779763 0.22395095 0.24434531
## [187] 0.28761193 0.33593890 0.53922295 0.11519909 0.94622994 0.62209974
## [193] 0.42695515 0.36608919 0.96127812 0.42745733 0.75261654 0.48275036
## [199] 0.67270407 0.86872809
## 
## $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")
#View(diagnoza)
#View(diagnozaDict)
pom_k <- diagnoza %>% na.omit() %>%
  filter(wojewodztwo == c("Pomorskie"))
#pom_k
pom_k <- as.data.frame(pom_k)

wykres1 <- ggplot(data=pom_k, aes(gp113, fill=eduk4_2013), gp64) +
    labs(title="Wykres gęstości dochodu osób pracujących w woj. pomorskim według przepracowanych godzin w tyg w zależności od wykształcenia", x = "Przepracowane godziny tygodniowo", y = "Dochód miesięczny netto") +
    geom_density() +
  theme(text = element_text(color = "#555555"), plot.title = element_text(size = 8)
        ,axis.title = element_text(size = 8, color = '#555555')
        ,axis.title.y = element_text(vjust = .5, angle = 90)
        ,axis.title.x = element_text(hjust = .5),legend.position="bottom",
        legend.title = element_text(size = 7)) +
  labs(fill='Wykształcenie')
wykres1

pom_edu <- diagnoza %>% na.omit() %>%
  filter(wojewodztwo == c("Pomorskie"))
#pom_edu


pom_edu <- as.data.frame(pom_edu)

wykres1 <- ggplot(data=pom_edu, aes(x=gp64, fill=status9_2013)) +
    labs(title="Dochód miesięczny netto", x = "Wykształcenie", y = "Wynagrodzenia") +
    geom_density() + 
  ggtitle("Wykres gęstości dochodu według edukacji i statusu społecznego w woj. pomorskim") +
  facet_wrap(~ eduk4_2013)  +
  theme(text = element_text(color = "#555555"), plot.title = element_text(size = 10)
        ,axis.title = element_text(size = 10, color = '#555555')
        ,axis.title.y = element_text(vjust = .5, angle = 90)
        ,axis.title.x = element_text(hjust = .5),legend.position="bottom",
        legend.title = element_text(size = 7)) +
  labs(fill='Status społeczny')
  
wykres1

pom_k_edu <- diagnoza %>% na.omit() %>%
  filter(wojewodztwo == c("Pomorskie"))
#pom_k_edu


pom_k_edu <- as.data.frame(pom_k_edu)

wykres1 <- ggplot(data=pom_k_edu, aes(x=gp64, fill=gp3)) +
    labs(title="Wykres gęstości dochodu według zadowolenia z życia oraz płci", x = "Zadowolenie z życia", y = "Wynagrodzenie") +
    geom_density() + 
  ggtitle("Dochód miesięczny w zależności od zadowolenia z obecnego życia w województwie pomorskim") +
  facet_wrap(~ plec) + 
  theme(text = element_text(color = "#555555"), plot.title = element_text(size = 9)
        ,axis.title = element_text(size = 9, color = '#555555')
        ,axis.title.y = element_text(vjust = .5, angle = 90)
        ,axis.title.x = element_text(hjust = .5),legend.position="bottom",
        legend.title = element_text(size = 9)) +
  labs(fill='Zadowolenie z obecnego życia')
  
wykres1

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