吴裕雄--天生自然 R语言开发学习：处理缺失数据的高级方法（续一）
2020-12-13 06:24
标签：data code which cti sum case package obs png 吴裕雄--天生自然 R语言开发学习：处理缺失数据的高级方法（续一） 标签：data code which cti sum case package obs png 原文地址：https://www.cnblogs.com/tszr/p/11177656.html
#-----------------------------------#
# R in Action (2nd ed): Chapter 18 #
# Advanced methods for missing data #
# requires packages VIM, mice #
# install.packages(c("VIM", mice)) #
#-----------------------------------#
par(ask=TRUE)
# load the dataset
data(sleep, package="VIM")
# list the rows that do not have missing values
sleep[complete.cases(sleep),]
# list the rows that have one or more missing values
sleep[!complete.cases(sleep),]
# tabulate missing values patters
library(mice)
md.pattern(sleep)
# plot missing values patterns
library("VIM")
aggr(sleep, prop=FALSE, numbers=TRUE)
matrixplot(sleep)
marginplot(sleep[c("Gest","Dream")], pch=c(20),
col=c("darkgray", "red", "blue"))
# use correlations to explore missing values
x is.na(sleep)))
head(sleep, n=5)
head(x, n=5)
y 0)]
cor(y)
cor(sleep, y, use="pairwise.complete.obs")
# complete case analysis (listwise deletion)
options(digits=1)
cor(na.omit(sleep))
fit na.omit(sleep))
summary(fit)
# multiple imputation
options(digits=3)
library(mice)
data(sleep, package="VIM")
imp )
fit Gest))
pooled pool(fit)
summary(pooled)
imp
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