按组划分的R- lm、cooks.distance和异常值
按组划分的R- lm、cooks.distance和异常值
提问于 2019-09-18 00:43:08
out-group的代码工作得很好：
url <- "https://raw.githubusercontent.com/selva86/datasets/master/ozone.csv"
ozone <- read.csv(url)
ozone <- head(ozone,20)
mod <- lm(ozone_reading ~ ., data=ozone)
cooksd <- cooks.distance(mod)
influential <- as.numeric(names(cooksd)[(cooksd > 4*mean(cooksd, na.rm=T))]) # influential row numbers
(ozone[influential, ]) # influential observations.根据我的新需求，我必须添加一个组，并需要查找每个组的异常值。我的代码示例如下所示。如何按组获取cooks.distance和异常值？请帮帮忙
url <- "https://raw.githubusercontent.com/selva86/datasets/master/ozone.csv"
ozone <- read.csv(url)
ozone <- head(ozone,20)
ozone$season <- c('summer','summer','summer','summer','summer','summer','summer','summer','summer','summer',
'winter','winter','winter','winter','winter','winter','winter','winter','winter','winter')这里我需要计算mod，cooksd和影响分组。
回答 1
Stack Overflow用户
回答已采纳
发布于 2019-09-18 01:13:54
简单地概括您的流程并使用by (tapply的面向对象包装器)调用它，它通过一个或多个因子对数据帧进行子集，并将子集传递给一个函数，以返回与不同组的数量相等的数据帧列表：
proc_cooks_outlier <- function(df) {
mod <- lm(ozone_reading ~ ., data=transform(df, season=NULL))
cooksd <- cooks.distance(mod)
# influential row numbers
influential <- as.integer(names(cooksd)[(cooksd > 4*mean(cooksd, na.rm=TRUE))])
return(df[complete.cases(df[influential,]),])
}
outlier_df_list <- by(ozone, ozone$season, FUN=proc_cooks_outlier)
# REFERENCE INDIVIDUAL DFs
outlier_df_list$summer
outlier_df_list$winter
...
# COMBINE ALL INTO ONE DF
master_outlier_df <- do.call(rbind, unname(outlier_df_list))页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/57978643
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