R - lm, cooks.distance & 离群值（按组）

Question

与外组合作的代码：

  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.

根据我的新要求，我必须添加一个组，并且需要为每个组找到异常值。我的代码示例如下所示。我如何得到 cooks.distance 和小组的异常值？请帮助

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')

这里我需要按组计算mod、cooksd和influential。

Answer 1

简单地概括您的过程并使用 by（tapply 的面向对象包装器）调用它，它通过一个或多个因素对数据帧进行子集化，并将子集传递到函数中以 return 等于不同组数的数据帧列表：

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))

R - lm, cooks.distance & 离群值（按组）

R - lm, cooks.distance & Outliers by Group

r

lm