{"id":3215,"date":"2023-07-18T15:10:25","date_gmt":"2023-07-18T15:10:25","guid":{"rendered":"https:\/\/statorials.org\/ja\/r-%e5%a4%89%e6%95%b0%e3%81%ae%e7%84%a1%e5%8a%b9%e3%81%aa%e5%9e%8b%e3%83%aa%e3%82%b9%e3%83%88\/"},"modified":"2023-07-18T15:10:25","modified_gmt":"2023-07-18T15:10:25","slug":"r-%e5%a4%89%e6%95%b0%e3%81%ae%e7%84%a1%e5%8a%b9%e3%81%aa%e5%9e%8b%e3%83%aa%e3%82%b9%e3%83%88","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/r-%e5%a4%89%e6%95%b0%e3%81%ae%e7%84%a1%e5%8a%b9%e3%81%aa%e5%9e%8b%e3%83%aa%e3%82%b9%e3%83%88\/","title":{"rendered":"R \u3067\u306e\u4fee\u6b63\u65b9\u6cd5: \u5909\u6570\u306e\u578b (\u30ea\u30b9\u30c8) \u304c\u7121\u52b9\u3067\u3059"},"content":{"rendered":"

<\/p>\n

\n

R \u3067\u767a\u751f\u3059\u308b\u53ef\u80fd\u6027\u306e\u3042\u308b\u30a8\u30e9\u30fc\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/span><\/p>\n

 Error in model.frame.default(formula = y ~ x, drop.unused.levels = TRUE): \n  invalid type (list) for variable 'x' \n<\/strong><\/pre>\n
\u3053\u306e\u30a8\u30e9\u30fc\u306f\u901a\u5e38\u3001R \u3067\u56de\u5e30\u30e2\u30c7\u30eb\u307e\u305f\u306f ANOVA \u30e2\u30c7\u30eb\u3092\u8fd1\u4f3c\u3057\u3088\u3046\u3068\u3057\u3001\u5909\u6570\u306e 1 \u3064\u3068\u3057\u3066\u30d9\u30af\u30c8\u30eb<\/strong>\u306e\u4ee3\u308f\u308a\u306b\u30ea\u30b9\u30c8\u3092<\/strong>\u4f7f\u7528\u3057\u305f\u3068\u304d\u306b\u767a\u751f\u3057\u307e\u3059\u3002<\/span><\/p>\n
\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001\u3053\u306e\u30a8\u30e9\u30fc\u3092\u5b9f\u969b\u306b\u4fee\u6b63\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n
\u30a8\u30e9\u30fc\u3092\u518d\u73fe\u3059\u308b\u65b9\u6cd5<\/strong><\/h2>\n
R \u3067\u5358\u7d14\u306a\u7dda\u5f62\u56de\u5e30\u30e2\u30c7\u30eb<\/a>\u3092\u5f53\u3066\u306f\u3081\u3088\u3046\u3068\u3057\u3066\u3044\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n
 #define variables\nx <- list(1, 4, 4, 5, 7, 8, 9, 10, 13, 14)\ny <- c(10, 13, 13, 14, 18, 20, 22, 24, 29, 31)<\/span>\n\n#attempt to fit regression model\nmodel <- lm(y ~ x)\n\nError in model.frame.default(formula = y ~ x, drop.unused.levels = TRUE): \n  invalid type (list) for variable 'x'\n<\/span><\/span><\/strong><\/span><\/pre>\n
 lm()<\/strong>\u95a2\u6570\u306f\u5165\u529b\u3068\u3057\u3066\u30d9\u30af\u30c8\u30eb\u306e\u307f\u3092\u53d7\u3051\u53d6\u308b\u3053\u3068\u304c\u3067\u304d\u3001\u5909\u6570 x \u306f\u73fe\u5728\u30ea\u30b9\u30c8\u3067\u3042\u308b\u305f\u3081\u3001\u30a8\u30e9\u30fc\u304c\u767a\u751f\u3057\u307e\u3059\u3002<\/span><\/p>\n
\u30a8\u30e9\u30fc\u3092\u56de\u907f\u3059\u308b\u65b9\u6cd5<\/strong><\/span><\/h2>\n
\u3053\u306e\u30a8\u30e9\u30fc\u3092\u56de\u907f\u3059\u308b\u6700\u3082\u7c21\u5358\u306a\u65b9\u6cd5\u306f\u3001\u5358\u7d14\u306bunlist()<\/a>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30ea\u30b9\u30c8\u5909\u6570\u3092\u30d9\u30af\u30c8\u30eb\u306b\u5909\u63db\u3059\u308b\u3053\u3068\u3067\u3059\u3002<\/span><\/span><\/p>\n
 #define variables\nx <- list(1, 4, 4, 5, 7, 8, 9, 10, 13, 14)\ny <- c(10, 13, 13, 14, 18, 20, 22, 24, 29, 31)\n\n#attempt to fit regression model\n<\/span>model <- lm(y ~ unlist(x))\n\n#view the model output<\/span>\nsummary(model)\n\nCall:\nlm(formula = y ~ unlist(x))\n\nResiduals:\n    Min 1Q Median 3Q Max \n-1.1282 -0.4194 -0.1087 0.2966 1.7068 \n\nCoefficients:\n            Estimate Std. Error t value Pr(>|t|)    \n(Intercept) 6.58447 0.55413 11.88 2.31e-06 ***\nunlist(x) 1.70874 0.06544 26.11 4.97e-09 ***\n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\nResidual standard error: 0.8134 on 8 degrees of freedom\nMultiple R-squared: 0.9884, Adjusted R-squared: 0.987 \nF-statistic: 681.8 on 1 and 8 DF, p-value: 4.97e-09\n<\/span><\/span><\/strong><\/span><\/pre>\n
\u4eca\u56de\u306funlist()<\/strong>\u3092\u4f7f\u7528\u3057\u3066\u5909\u6570 x \u3092\u30d9\u30af\u30c8\u30eb\u306b\u5909\u63db\u3057\u305f\u305f\u3081\u3001\u30a8\u30e9\u30fc\u306a\u3057\u3067\u5358\u7d14\u306a\u7dda\u5f62\u56de\u5e30\u30e2\u30c7\u30eb\u3092\u5f53\u3066\u306f\u3081\u308b\u3053\u3068\u304c\u3067\u304d\u305f\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n
 #define variables\nx1 <- list(1, 4, 4, 5, 7, 8, 9, 10, 13, 14)\nx2 <- list(20, 16, 16, 15, 16, 12, 10, 8, 8, 4)\ny <- c(10, 13, 13, 14, 18, 20, 22, 24, 29, 31)\n\n#fit multiple linear regression model\n<\/span>model <- lm(y ~ unlist(x1) + unlist(x2))\n\n#view the model output\n<\/span>summary(model)\n\nCall:\nlm(formula = y ~ unlist(x1) + unlist(x2))\n\nResiduals:\n    Min 1Q Median 3Q Max \n-1.1579 -0.4211 -0.1386 0.3108 1.7130 \n\nCoefficients:\n            Estimate Std. Error t value Pr(>|t|)    \n(Intercept) 8.34282 4.44971 1.875 0.102932    \nunlist(x1) 1.61339 0.24899 6.480 0.000341 ***\nunlist(x2) -0.08346 0.20937 -0.399 0.702044    \n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\nResidual standard error: 0.8599 on 7 degrees of freedom\nMultiple R-squared: 0.9887, Adjusted R-squared: 0.9854 \nF-statistic: 305.1 on 2 and 7 DF, p-value: 1.553e-07<\/span><\/span><\/strong><\/span><\/pre>\n
\u3053\u3053\u3067\u3082\u3001\u30ea\u30b9\u30c8\u5185\u306e\u5404\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u30d9\u30af\u30c8\u30eb\u306b\u5909\u63db\u3057\u305f\u305f\u3081\u3001\u30a8\u30e9\u30fc\u306f\u767a\u751f\u3057\u307e\u305b\u3093\u3002<\/span><\/span><\/p>\n
\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h3>\n
\u6b21\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001R \u3067\u4ed6\u306e\u4e00\u822c\u7684\u306a\u64cd\u4f5c\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n
 R \u3067 glm \u51fa\u529b\u3092\u89e3\u91c8\u3059\u308b\u65b9\u6cd5<\/a>
R \u3067 ANOVA \u7d50\u679c\u3092\u89e3\u91c8\u3059\u308b\u65b9\u6cd5<\/a>
R \u306e\u51e6\u7406\u65b9\u6cd5 \u8b66\u544a: glm.fit: \u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u304c\u53ce\u675f\u3057\u307e\u305b\u3093\u3067\u3057\u305f<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
R \u3067\u767a\u751f\u3059\u308b\u53ef\u80fd\u6027\u306e\u3042\u308b\u30a8\u30e9\u30fc\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002 Error in model.frame.default(formula = y ~ x, drop.unused.levels = TRUE): invalid ty […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-3215","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"\nR \u3067\u4fee\u6b63\u3059\u308b\u65b9\u6cd5: \u5909\u6570\u306e\u578b (\u30ea\u30b9\u30c8) \u304c\u7121\u52b9\u3067\u3059 - \u7d71\u8a08<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001R \u3067\u6b21\u306e\u30a8\u30e9\u30fc\u3092\u4fee\u6b63\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059: \u5909\u6570\u306e\u578b (\u30ea\u30b9\u30c8) \u304c\u7121\u52b9\u3067\u3059\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ja\/r-\u5909\u6570\u306e\u7121\u52b9\u306a\u578b\u30ea\u30b9\u30c8\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"R \u3067\u4fee\u6b63\u3059\u308b\u65b9\u6cd5: \u5909\u6570\u306e\u578b (\u30ea\u30b9\u30c8) \u304c\u7121\u52b9\u3067\u3059 - 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