{"id":3366,"date":"2024-03-03T23:05:08","date_gmt":"2024-03-03T14:05:08","guid":{"rendered":"https:\/\/plaza.umin.ac.jp\/~OIO\/?p=3366"},"modified":"2024-03-03T23:05:08","modified_gmt":"2024-03-03T14:05:08","slug":"r-%e7%a2%ba%e7%8e%87%e5%af%86%e5%ba%a6%e9%96%a2%e6%95%b0%e3%81%a8%e5%88%86%e5%b8%83%e6%af%8d%e6%95%b0%e3%81%ae%e6%8e%a8%e5%ae%9a","status":"publish","type":"post","link":"https:\/\/plaza.umin.ac.jp\/~OIO\/?p=3366","title":{"rendered":"R \u78ba\u7387\u5bc6\u5ea6\u95a2\u6570\u3068\u5206\u5e03\u6bcd\u6570\u306e\u63a8\u5b9a"},"content":{"rendered":"

\u306f\u3058\u3081\u306b<\/h1>\n

\u624b\u6301\u3061\u306e\u5358\u5909\u91cf\u306e\u5206\u5e03\u3092\u78ba\u7387\u5bc6\u5ea6\u95a2\u6570\u306b\u5f53\u3066\u306f\u3081\u3066\u6bcd\u6570\u3092\u63a8\u5b9a\u3059\u308b\uff08\u3088\u304f\u308f\u304b\u3089\u306a\u3044\uff09<\/p>\n

\u4f7f\u3046\u30c7\u30fc\u30bf\u306f\u4ed6\u306e\u30da\u30fc\u30b8\u3067\u4f5c\u6210<\/a>\u3057\u305fdf.testDATA<\/p>\n

\u30b9\u30af\u30ea\u30d7\u30c8<\/h1>\n
library(fitdistrplus)\r\n# \u5206\u5e03\u306e\u30c6\u30b9\u30c8\r\nx <- df.testDATA$Time2Onset\r\ny <- max(df.testDATA$Time2Onset)\r\nmin(df.testDATA$Time2Onset)\r\n################ distribution test ################ \r\n\r\nnormmlefit <- fitdist(x, \"norm\", \"mle\"); fit <- normmlefit; gofstat(fit); plot(fit)\r\nlnormmlefit <- fitdist(x + 0.1, \"lnorm\", \"mle\"); fit <- lnormmlefit; gofstat(fit); plot(fit)\r\npoismlefit <- fitdist(x, \"pois\", \"mle\"); fit <- poismlefit; gofstat(fit); plot(fit)\r\nexpmlefit <- fitdist(x, \"exp\", \"mle\"); fit <- expmlefit; gofstat(fit); plot(fit)\r\ngammammefit <- fitdist(x, \"gamma\", \"mme\"); fit <- gammamlefit; gofstat(fit); plot(fit)\r\nnbinommlefit <- fitdist(x, \"nbinom\", \"mle\"); fit <- nbinommlefit; gofstat(fit); plot(fit)\r\ngeommlefit <- fitdist(x, \"geom\", \"mle\"); fit <- geommlefit; gofstat(fit); plot(fit)\r\nbetammefit <- fitdist(x\/y, \"beta\", \"mme\"); fit <- betamlefit; gofstat(fit); plot(fit)\r\nunifmlefit <- fitdist(x, \"unif\", \"mle\"); fit <- unifmlefit; gofstat(fit); plot(fit)\r\nlogismlefit <- fitdist(x, \"logis\", \"mle\"); fit <- logismlefit; gofstat(fit); plot(fit)<\/pre>\n
\u7d50\u679c<\/h1>\n
\u3088\u304f\u30d5\u30a3\u30c3\u30c8\u3057\u3066\u305d\u3046\u306a\u306e\u306fbeta\u304bgamma\u306e\u69d8\u3067\u3059<\/p>\n
\u30ed\u30b8\u30b9\u30c6\u30a3\u30c3\u30af\u5206\u5e03<\/h2>\n
\"\"<\/p>\n
Fitting of the distribution ' logis ' by maximum likelihood \r\nParameters : \r\n         estimate Std. Error\r\nlocation 58.31789   2.418478\r\nscale    45.17608   1.249104\r\nLoglikelihood:  -5863.559   AIC:  11731.12   BIC:  11740.93 \r\nCorrelation matrix:\r\n          location     scale\r\nlocation 1.0000000 0.1570439\r\nscale    0.1570439 1.0000000<\/pre>\n
\u4e00\u69d8\u306e\u5206\u5e03\uff08\u5b9a\u6570\uff09<\/h2>\n
\"\"<\/p>\n
Fitting of the distribution ' unif ' by maximum likelihood \r\nParameters : \r\n    estimate Std. Error\r\nmin        0         NA\r\nmax      682         NA\r\nLoglikelihood:  -6525.03   AIC:  13054.06   BIC:  13063.87 \r\nCorrelation matrix:\r\n[1] NA<\/pre>\n
beta\u5206\u5e03<\/h2>\n
\"\"<\/p>\n
Fitting of the distribution ' beta ' by matching moments \r\nParameters : \r\n        estimate\r\nshape1 0.4604008\r\nshape2 3.6574364\r\nLoglikelihood:  NaN   AIC:  NaN   BIC:  NaN<\/pre>\n
geom\u5206\u5e03<\/h2>\n
\"\"<\/p>\n
Fitting of the distribution ' geom ' by maximum likelihood \r\nParameters : \r\n       estimate   Std. Error\r\nprob 0.01294465 0.0004042749\r\nLoglikelihood:  -5340.572   AIC:  10683.14   BIC:  10688.05<\/pre>\n
 <\/p>\n
\u8ca0\u306e\u4e8c\u9805\u5206\u5e03<\/h2>\n
\"\"<\/p>\n
Fitting of the distribution ' nbinom ' by maximum likelihood \r\nParameters : \r\n       estimate Std. Error\r\nsize  0.7293184 0.02936535\r\nmu   76.2394754 2.83607459\r\nLoglikelihood:  -5307.489   AIC:  10618.98   BIC:  10628.79 \r\nCorrelation matrix:\r\n             size           mu\r\nsize 1.0000000000 0.0001760878\r\nmu   0.0001760878 1.0000000000<\/pre>\n
 <\/p>\n
gamma\u5206\u5e03<\/h2>\n
\"\"<\/p>\n
Fitting of the distribution ' gamma ' by matching moments \r\nParameters : \r\n         estimate\r\nshape 0.644237078\r\nrate  0.008448789\r\nLoglikelihood:  Inf   AIC:  -Inf   BIC:  -Inf<\/pre>\n
 <\/p>\n
\u6307\u6570\u5206\u5e03<\/h2>\n
\"\"<\/p>\n
Fitting of the distribution ' exp ' by maximum likelihood \r\nParameters : \r\n       estimate   Std. Error\r\nrate 0.01311441 0.0004122862\r\nLoglikelihood:  -5334.044   AIC:  10670.09   BIC:  10675<\/pre>\n
 <\/p>\n
\u30dd\u30ef\u30bd\u30f3\u5206\u5e03<\/h2>\n
\"\"<\/p>\n
Fitting of the distribution ' pois ' by maximum likelihood \r\nParameters : \r\n       estimate Std. Error\r\nlambda   76.252  0.2761377\r\nLoglikelihood:  -48448.44   AIC:  96898.87   BIC:  96903.78<\/pre>\n
 <\/p>\n
\u5bfe\u6570\u6b63\u898f\u5206\u5e03<\/h2>\n
\"\"<\/p>\n
Fitting of the distribution ' lnorm ' by maximum likelihood \r\nParameters : \r\n        estimate Std. Error\r\nmeanlog 3.477753 0.05160282\r\nsdlog   1.631824 0.03648864\r\nLoglikelihood:  -5386.39   AIC:  10776.78   BIC:  10786.6 \r\nCorrelation matrix:\r\n        meanlog sdlog\r\nmeanlog       1     0\r\nsdlog         0     1<\/pre>\n
 <\/p>\n
 <\/p>\n
\u6b63\u898f\u5206\u5e03<\/h2>\n
\"\"<\/p>\n
Fitting of the distribution ' norm ' by maximum likelihood \r\nParameters : \r\n     estimate Std. Error\r\nmean 76.25200   3.004195\r\nsd   95.00104   2.124288\r\nLoglikelihood:  -5972.826   AIC:  11949.65   BIC:  11959.47 \r\nCorrelation matrix:\r\n     mean sd\r\nmean    1  0\r\nsd      0  1<\/pre>\n","protected":false},"excerpt":{"rendered":"
\u306f\u3058\u3081\u306b \u624b\u6301\u3061\u306e\u5358\u5909\u91cf\u306e\u5206\u5e03\u3092\u78ba\u7387\u5bc6\u5ea6\u95a2\u6570\u306b\u5f53\u3066\u306f\u3081\u3066\u6bcd\u6570\u3092\u63a8\u5b9a\u3059\u308b\uff08\u3088\u304f\u308f\u304b\u3089\u306a\u3044\uff09 \u4f7f\u3046\u30c7\u30fc\u30bf\u306f\u4ed6\u306e\u30da\u30fc\u30b8\u3067\u4f5c\u6210\u3057\u305fdf.testDATA \u30b9\u30af\u30ea\u30d7\u30c8 library(fitdistrplus) # \u5206\u5e03\u306e\u30c6\u30b9\u30c8 …<\/p>\n","protected":false},"author":1,"featured_media":3372,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[5],"tags":[],"class_list":["post-3366","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-miscellaneous"],"jetpack_featured_media_url":"https:\/\/plaza.umin.ac.jp\/~OIO\/wp-content\/uploads\/2024\/03\/b70ef1e75b315282b16531f261ae6abc.png","jetpack_shortlink":"https:\/\/wp.me\/p9b6zl-Si","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/plaza.umin.ac.jp\/~OIO\/index.php?rest_route=\/wp\/v2\/posts\/3366","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/plaza.umin.ac.jp\/~OIO\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/plaza.umin.ac.jp\/~OIO\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/plaza.umin.ac.jp\/~OIO\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/plaza.umin.ac.jp\/~OIO\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3366"}],"version-history":[{"count":0,"href":"https:\/\/plaza.umin.ac.jp\/~OIO\/index.php?rest_route=\/wp\/v2\/posts\/3366\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/plaza.umin.ac.jp\/~OIO\/index.php?rest_route=\/wp\/v2\/media\/3372"}],"wp:attachment":[{"href":"https:\/\/plaza.umin.ac.jp\/~OIO\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3366"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/plaza.umin.ac.jp\/~OIO\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3366"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/plaza.umin.ac.jp\/~OIO\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3366"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}