用格子绘制回归线

Question

我在这里遇到一些麻烦，请帮助我。 我有这个数据

set.seed(4)
mydata <- data.frame(var = rnorm(100),
                     temp = rnorm(100),
                     subj = as.factor(rep(c(1:10),5)),
                     trt = rep(c("A","B"), 50))

这个适合他们的模型

lm  <- lm(var ~ temp * subj, data = mydata)

我想用 lattice 绘制结果，并使用我的模型预测回归线。为此，我正在使用这种方法，概述了D. Sarkar的“电力使用的格子技巧”

temp_rng <- range(mydata$temp, finite = TRUE)

grid <- expand.grid(temp = do.breaks(temp_rng, 30),
                    subj = unique(mydata$subj),
                    trt = unique(mydata$trt))

model <- cbind(grid, var = predict(lm, newdata = grid))

orig <- mydata[c("var","temp","subj","trt")]

combined <- make.groups(original = orig, model = model)


xyplot(var ~ temp | subj, 
       data = combined,
       groups = which,
       type = c("p", "l"),
       distribute.type = TRUE
       )

到目前为止，每件事都很好，但我还想为两种治疗trt=1和trt=2的数据点指定填充颜色。

所以我编写了这段代码，工作正常，但是当绘制回归线时，面板函数似乎无法识别该类型......

my.fill <- c("black", "grey")

plot <- with(combined,
        xyplot(var ~ temp | subj,
              data = combined,
              group = combined$which,
              type = c("p", "l"),
              distribute.type = TRUE,
              panel = function(x, y, ..., subscripts){
                     fill <- my.fill[combined$trt[subscripts]] 
                     panel.xyplot(x, y, pch = 21, fill = my.fill, col = "black")
                     },
             key = list(space = "right",
                     text = list(c("trt1", "trt2"), cex = 0.8),
                     points = list(pch = c(21), fill = c("black", "grey")),
                     rep = FALSE)
                     )
      )
plot

我还尝试在panel.xyplot中移动类型和分发类型，并将panel.xyplot中的数据子集化为此类

plot <- with(combined,
        xyplot(var ~ temp | subj,
              data = combined,
              panel = function(x, y, ..., subscripts){
                     fill <- my.fill[combined$trt[subscripts]] 
                     panel.xyplot(x[combined$which=="original"], y[combined$which=="original"], pch = 21, fill = my.fill, col = "black")
                     panel.xyplot(x[combined$which=="model"], y[combined$which=="model"], type = "l", col = "black")
                     },
             key = list(space = "right",
                     text = list(c("trt1", "trt2"), cex = 0.8),
                     points = list(pch = c(21), fill = c("black", "grey")),
                     rep = FALSE)
                     )
      )
plot

但也没有成功。

任何人都可以帮助我将预测值绘制为一条线而不是点吗？

Answer 1

这可能是latticeExtra包的工作。

library(latticeExtra)
p1 <- xyplot(var ~ temp | subj, data=orig, panel=function(..., subscripts) {
  fill <- my.fill[combined$trt[subscripts]] 
  panel.xyplot(..., pch=21, fill=my.fill, col="black")
})
p2 <- xyplot(var ~ temp | subj, data=model, type="l")
p1+p2

我不确定你的第一次尝试是怎么回事，但带有下标的那个没有用，因为x和y是subj数据的子集，所以使用基于{{1的向量对它们进行子集化不会像你想象的那样工作。试试这个。

combined

Answer 2

仅在原始数据上使用panel.lmline功能可能更容易：

xyplot(var ~ temp | subj,
        data = orig,
        panel = function(x,y,...,subscripts){
            fill <- my.fill[orig$trt[subscripts]]
            panel.xyplot(x, y, pch = 21, fill = my.fill,col = "black")
            panel.lmline(x,y,col = "salmon")
        },
        key = list(space = "right",
                     text = list(c("trt1", "trt2"), cex = 0.8),
                     points = list(pch = c(21), fill = c("black", "grey")),
                     rep = FALSE)
)

Answer 3

这可能是微不足道的，但您可以尝试：

xyplot(... , type=c("p","l","r"))

“p”添加点，“l”用虚线连接它们，“r”适合您的数据线性模型。仅type="r"将仅绘制回归线而不显示数据点。