使用莱迪思(或其他东西)在R中的lme4绘制回归结果 [英] Plotting Regression results from lme4 in R using Lattice (or something else)

问题描述

由于有了上一个答案.现在，我对每个州都有回归拟合，我想使用晶格为每个州绘制QQ图.我还想以晶格格式绘制每个状态的误差图.如何使用lme4回归的结果制作格子图?

I have fit a regression using lme4 thanks to a previous answer. Now that I have a regression fit for each state I'd like to use lattice to plot QQ plots for each state. I would also like to plot error plots for each state in a lattice format. How do I make a lattice plot using the results of a lme4 regression?

下面是一个使用两个状态的简单示例(是的，我喜欢一个很好的称呼).我想制作一个由对象拟合而成的两块面板的格子.

Below is a simple sample (yeah, I like a good alliteration) using two states. I would like to make a two panel lattice made from the object fits.

library(lme4)
d <- data.frame(state=rep(c('NY', 'CA'), c(10, 10)), year=rep(1:10, 2), response=c(rnorm(10), rnorm(10)))
fits <- lmList(response ~ year | state, data=d)

推荐答案

我建议使用更通用的plyr软件包，而不是使用lmList.

Instead of using lmList, I'd recommend the more general plyr package.

library(plyr)

d <- data.frame(
 state = rep(c('NY', 'CA'), c(10, 10)), 
 year = rep(1:10, 2), 
 response = c(rnorm(10), rnorm(10))
)

# Create a list of models
# dlply = data frame -> list
models <- dlply(d, ~ state, function(df) { 
  lm(response ~ year, data = df)
})

# Extract the coefficients in a useful form
# ldply = list -> data frame
ldply(models, coef)

# We can get the predictions in a similar way, but we need
# to cast to a data frame so the numbers come out as rows,
# not columns.
predictions <- ldply(models, as.data.frame(predict))

predictions是常规R数据帧，因此易于绘制.

predictions is a regular R data frame and so is easy to plot.

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