{"id":2469,"date":"2023-07-22T03:17:44","date_gmt":"2023-07-22T03:17:44","guid":{"rendered":"https:\/\/statorials.org\/ja\/python%e3%81%a6%e3%82%99%e3%81%ae%e3%82%af%e3%82%99%e3%83%ac%e3%83%b3%e3%82%b7%e3%82%99%e3%83%a3%e3%83%bc%e5%9b%a0%e6%9e%9c%e9%96%a2%e4%bf%82%e3%83%86%e3%82%b9%e3%83%88\/"},"modified":"2023-07-22T03:17:44","modified_gmt":"2023-07-22T03:17:44","slug":"python%e3%81%a6%e3%82%99%e3%81%ae%e3%82%af%e3%82%99%e3%83%ac%e3%83%b3%e3%82%b7%e3%82%99%e3%83%a3%e3%83%bc%e5%9b%a0%e6%9e%9c%e9%96%a2%e4%bf%82%e3%83%86%e3%82%b9%e3%83%88","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/python%e3%81%a6%e3%82%99%e3%81%ae%e3%82%af%e3%82%99%e3%83%ac%e3%83%b3%e3%82%b7%e3%82%99%e3%83%a3%e3%83%bc%e5%9b%a0%e6%9e%9c%e9%96%a2%e4%bf%82%e3%83%86%e3%82%b9%e3%83%88\/","title":{"rendered":"Python \u3067\u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u56e0\u679c\u95a2\u4fc2\u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"

<\/p>\n

\n

\u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u56e0\u679c\u95a2\u4fc2\u30c6\u30b9\u30c8\u306f\u3001<\/strong>\u3042\u308b\u6642\u7cfb\u5217\u304c\u5225\u306e\u6642\u7cfb\u5217\u306e\u4e88\u6e2c\u306b\u5f79\u7acb\u3064\u304b\u3069\u3046\u304b\u3092\u5224\u65ad\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n

\u3053\u306e\u691c\u5b9a\u3067\u306f\u3001\u6b21\u306e\u5e30\u7121\u4eee\u8aac\u3068\u5bfe\u7acb\u4eee\u8aac\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/span><\/p>\n

\u5e30\u7121\u4eee\u8aac (H 0<\/sub> ):<\/strong>\u6642\u7cfb\u5217x \u306f<\/em>\u6642\u7cfb\u5217y<\/em>\u3092\u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u306b\u5f15\u304d\u8d77\u3053\u3055\u306a\u3044<\/span><\/p>\n

\u5bfe\u7acb\u4eee\u8aac ( HA<\/sub> ):<\/strong>\u6642\u7cfb\u5217x<\/em>\u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u306e\u6642\u7cfb\u5217\u304cy<\/em>\u3092\u5f15\u304d\u8d77\u3053\u3059<\/span><\/p>\n

\u300c\u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u539f\u56e0\u300d\u3068\u3044\u3046\u7528\u8a9e\u306f\u3001\u4e00\u5b9a\u306e\u9045\u308c\u3092\u6301\u3063\u3066\u6642\u7cfb\u5217x<\/em>\u306e\u5024\u3092\u77e5\u308b\u3053\u3068\u304c\u3001\u5f8c\u306e\u671f\u9593\u306e\u6642\u7cfb\u5217y<\/em>\u306e\u5024\u3092\u4e88\u6e2c\u3059\u308b\u306e\u306b\u5f79\u7acb\u3064\u3053\u3068\u3092\u610f\u5473\u3057\u307e\u3059\u3002<\/span><\/p>\n

\u3053\u306e\u691c\u5b9a\u3067\u306f\u3001\u5bfe\u5fdc\u3059\u308bp \u5024<\/a>\u3092\u542b\u3080 F \u691c\u5b9a\u7d71\u8a08\u91cf\u304c\u751f\u6210\u3055\u308c\u307e\u3059\u3002 p \u5024\u304c<\/span>\u7279\u5b9a\u306e\u6709\u610f\u6c34\u6e96 (\u3064\u307e\u308a\u3001\u03b1 = 0.05) \u3092\u4e0b\u56de\u3063\u3066\u3044\u308b\u5834\u5408\u3001\u5e30\u7121\u4eee\u8aac\u3092\u68c4\u5374\u3057\u3001\u6642\u7cfb\u5217x<\/em>\u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u304c\u6642\u7cfb\u5217 y \u3092\u5f15\u304d\u8d77\u3053\u3059\u3068\u4e3b\u5f35\u3059\u308b\u5341\u5206\u306a\u8a3c\u62e0\u304c\u3042\u308b\u3068\u7d50\u8ad6\u4ed8\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n

statsmodels \u30d1\u30c3\u30b1\u30fc\u30b8\u306egrangercausalitytests()<\/a>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001Python \u3067\u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u56e0\u679c\u95a2\u4fc2\u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n

 from<\/span> statsmodels. tsa<\/span> . stattools<\/span> import<\/span> grangercausalitytests\n\n#perform Granger-Causality test<\/span>\ngrangercausalitytests(df[[' column1<\/span> ', ' column2<\/span> ']], maxlag=[ 3<\/span> ])\n<\/strong><\/pre>\n
 maxlag \u306f\u3001<\/strong>\u6700\u521d\u306e\u6642\u7cfb\u5217\u3067\u4f7f\u7528\u3059\u308b\u30e9\u30b0\u306e\u6570\u3092\u6307\u5b9a\u3059\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/span><\/p>\n
\u6b21\u306e\u30b9\u30c6\u30c3\u30d7\u30d0\u30a4\u30b9\u30c6\u30c3\u30d7\u306e\u4f8b\u306f\u3001\u3053\u306e\u95a2\u6570\u3092\u5b9f\u969b\u306b\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n
\u30b9\u30c6\u30c3\u30d7 1: \u30c7\u30fc\u30bf\u3092\u30ed\u30fc\u30c9\u3059\u308b<\/strong><\/span><\/h3>\n
\u3053\u306e\u4f8b\u3067\u306f\u30011930 \u5e74\u304b\u3089 1983 \u5e74\u307e\u3067\u306b\u7c73\u56fd\u3067\u88fd\u9020\u3055\u308c\u305f\u5375\u306e\u6570\u3068\u9d8f\u306e\u6570\u306e\u5024\u3092\u542b\u3080\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#define URL where dataset is located\n<\/span>url = \"https:\/\/raw.githubusercontent.com\/Statorials\/Miscellaneous\/main\/chicken_egg.txt\"\n\n#read in dataset as pandas DataFrame\n<\/span>df = pd. read_csv<\/span> (url, sep=\" \")\n\n#view first five rows of DataFrame\n<\/span>df. head<\/span> ()\n\n\tyear chicken egg\n0 1930 468491 3581\n1 1931 449743 3532\n2 1932 436815 3327\n3 1933 444523 3255\n4 1934 433937 3156\n<\/strong><\/pre>\n
\u30b9\u30c6\u30c3\u30d7 2: \u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u56e0\u679c\u95a2\u4fc2\u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3059\u308b<\/strong><\/span><\/h3>\n
\u6b21\u306b\u3001 grangercausalitytests<\/strong> ()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u56e0\u679c\u95a2\u4fc2\u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3057\u3001\u4f5c\u3089\u308c\u305f\u5375\u306e\u6570\u304c\u5c06\u6765\u306e\u9d8f\u306e\u6570\u3092\u4e88\u6e2c\u3067\u304d\u308b\u304b\u3069\u3046\u304b\u3092\u78ba\u8a8d\u3057\u307e\u3059\u3002 3 \u3064\u306e\u30aa\u30d5\u30bb\u30c3\u30c8\u3092\u4f7f\u7528\u3057\u3066\u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/span><\/p>\n
 from<\/span> statsmodels. tsa<\/span> . stattools<\/span> import<\/span> grangercausalitytests<\/span>\n\n#perform Granger-Causality test<\/span>\ngrangercausalitytests(df[[' chicken<\/span> ', ' egg<\/span> ']], maxlag=[ 3<\/span> ])\n\nGranger Causality\nnumber of lags (no zero) 3\nssr based F test: F=5.4050, p=0.0030, df_denom=44, df_num=3\nssr based chi2 test: chi2=18.7946, p=0.0003, df=3\nlikelihood ratio test: chi2=16.0003, p=0.0011, df=3\nparameter F test: F=5.4050, p=0.0030, df_denom=44, df_num=3<\/strong><\/pre>\n
 F \u691c\u5b9a\u7d71\u8a08\u91cf\u306f5.405<\/strong>\u3067\u3042\u308a\u3001\u5bfe\u5fdc\u3059\u308b p \u5024\u306f0.0030<\/strong>\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n
 p \u5024\u306f 0.05 \u672a\u6e80\u3067\u3042\u308b\u305f\u3081\u3001\u691c\u5b9a\u306e\u5e30\u7121\u4eee\u8aac\u3092\u68c4\u5374\u3057\u3001\u5375\u306e\u6570\u3092\u77e5\u308b\u3053\u3068\u304c\u5c06\u6765\u306e\u9d8f\u306e\u6570\u3092\u4e88\u6e2c\u3059\u308b\u306e\u306b\u5f79\u7acb\u3064\u3068\u7d50\u8ad6\u4ed8\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
\u30b9\u30c6\u30c3\u30d7 3: \u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u56e0\u679c\u95a2\u4fc2\u30c6\u30b9\u30c8\u3092\u9006\u306b\u5b9f\u884c\u3059\u308b<\/strong><\/span><\/h3>\n
\u691c\u5b9a\u306e\u5e30\u7121\u4eee\u8aac\u306f\u68c4\u5374\u3055\u308c\u307e\u3057\u305f\u304c\u3001\u5b9f\u969b\u306b\u306f\u3001\u9006\u306e\u56e0\u679c\u95a2\u4fc2\u306e\u30b1\u30fc\u30b9\u304c\u767a\u751f\u3059\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002\u3064\u307e\u308a\u3001\u9d8f\u306e\u6570\u306b\u3088\u3063\u3066\u5375\u306e\u6570\u304c\u5909\u5316\u3059\u308b\u53ef\u80fd\u6027\u304c\u3042\u308b\u306e\u3067\u3059\u3002<\/span><\/p>\n
\u3053\u306e\u53ef\u80fd\u6027\u3092\u6392\u9664\u3059\u308b\u306b\u306f\u3001\u30cb\u30ef\u30c8\u30ea\u3092\u4e88\u6e2c\u5909\u6570\u3068\u3057\u3066\u3001\u5375\u3092\u5fdc\u7b54\u5909\u6570<\/a>\u3068\u3057\u3066\u4f7f\u7528\u3057\u3066\u3001\u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u56e0\u679c\u95a2\u4fc2\u691c\u5b9a\u3092\u9006\u306b\u5b9f\u884c\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n
 from<\/span> statsmodels. tsa<\/span> . stattools<\/span> import<\/span> grangercausalitytests<\/span>\n\n#perform Granger-Causality test<\/span>\ngrangercausalitytests(df[[' egg<\/span> ', ' chicken<\/span> ']], maxlag=[ 3<\/span> ])\n\nGranger Causality\nnumber of lags (no zero) 3\nssr based F test: F=0.5916, p=0.6238, df_denom=44, df_num=3\nssr based chi2 test: chi2=2.0572, p=0.5606, df=3\nlikelihood ratio test: chi2=2.0168, p=0.5689, df=3\nparameter F test: F=0.5916, p=0.6238, df_denom=44, df_num=3\n<\/strong><\/pre>\n
 F \u691c\u5b9a\u7d71\u8a08\u91cf\u306f0.5916<\/strong>\u3067\u3001\u5bfe\u5fdc\u3059\u308b p \u5024\u306f0.6238<\/strong>\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n
 p \u5024\u306f 0.05 \u672a\u6e80\u3067\u306f\u306a\u3044\u305f\u3081\u3001\u5e30\u7121\u4eee\u8aac\u3092\u68c4\u5374\u3067\u304d\u307e\u305b\u3093\u3002\u8a00\u3044\u63db\u3048\u308c\u3070\u3001\u9d8f\u306e\u6570\u306f\u5c06\u6765\u306e\u5375\u306e\u6570\u3092\u4e88\u6e2c\u3059\u308b\u3082\u306e\u3067\u306f\u3042\u308a\u307e\u305b\u3093\u3002<\/span><\/p>\n
\u3057\u305f\u304c\u3063\u3066\u3001\u5375\u306e\u6570\u3092\u77e5\u308b\u3053\u3068\u306f\u3001\u5c06\u6765\u306e\u9d8f\u306e\u6570\u3092\u4e88\u6e2c\u3059\u308b\u306e\u306b\u5f79\u7acb\u3064\u3068\u7d50\u8ad6\u4ed8\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h3>\n
\u6b21\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python \u3067\u6642\u7cfb\u5217\u3092\u4f7f\u7528\u3057\u3066\u4ed6\u306e\u4e00\u822c\u7684\u306a\u30bf\u30b9\u30af\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n
 Seaborn \u3067\u6642\u7cfb\u5217\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5<\/a>
Matplotlib \u3067\u6642\u7cfb\u5217\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u56e0\u679c\u95a2\u4fc2\u30c6\u30b9\u30c8\u306f\u3001\u3042\u308b\u6642\u7cfb\u5217\u304c\u5225\u306e\u6642\u7cfb\u5217\u306e\u4e88\u6e2c\u306b\u5f79\u7acb\u3064\u304b\u3069\u3046\u304b\u3092\u5224\u65ad\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002 \u3053\u306e\u691c\u5b9a\u3067\u306f\u3001\u6b21\u306e\u5e30\u7121\u4eee\u8aac\u3068\u5bfe\u7acb\u4eee\u8aac\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002 \u5e30\u7121\u4eee\u8aac (H 0 ):\u6642\u7cfb\u5217x \u306f\u6642\u7cfb\u5217y\u3092\u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u306b\u5f15 […]<\/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-2469","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"\nPython \u3067\u30b0\u30ec\u30f3\u30b8\u30e3\u30fc\u56e0\u679c\u95a2\u4fc2\u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5 - 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