我已经创建了想要得到的基本图形,只是无法弄清楚如何根据USArrests数据集中的谋杀属性的平均值在图形中添加一条线。之后,我还需要根据状态名称的高低来给它们上色。
我拥有的图表:https://ibb.co/V3VkYt4
我需要的图形:https://ibb.co/4TTnQM1
我尝试添加带有Murder属性的abline作为输入,并且该行显示在图形的外部,不确定我在做什么错。
library(lattice)
textPlot <- function()
{
data <- cbind(rownames(USArrests), USArrests)
names(data) <- c("State", names(data)[2:5])
averageM <- mean(USArrests$Murder)
xyplot(Murder~UrbanPop, data,
groups=State, panel=drawText,
main="Murder vs. Urban Population")
}
drawText <- function(x,y,groups,...)
{
panel.text(x=x,y=y,label=groups,cex=y/10)
}
答案 0 :(得分:1)
您的图形似乎显示了一条倾斜的回归线,而不是水平线。莱迪思可以直接从xyplot
的变量或panel.lmline
的回归模型(或常数)在panel.abline
中添加回归线。需要更多的工作来对高于或低于选定谋杀率的州进行分类。这是一种使用显示两种回归线类型的格子进行处理的方法。
# Load the lattice package, create data.frame with state names from USAarrests
library(lattice)
df <- data.frame(State = rownames(USArrests), USArrests)
# Determine regression and mean murder rate outside of xyplot()
# However, these operations don't have to be done outside of the lattice function
fm <- lm(Murder ~ UrbanPop, df)
averageM <- mean(USArrests$Murder)
# Add a variable to the data.frame indicating the classification
df$type <- factor(ifelse(df$Murder < fm$fitted, "low", "high"))
# Plot via lattice with explicit panel() function
xyplot(Murder ~ UrbanPop, data = df,
panel = function(x, y, ...) {
panel.abline(fm, col = "red", lwd = 2)
# panel.lmline(x, y, col = "red", lwd = 2) # This would do the same
panel.abline(h = averageM, col = "red", lty = 2, lwd = 2)
# panel.abline(h = mean(y), col = "red", lty = 2, lwd = 2) # This would do the same
panel.text(x, y, labels = df$State, cex = y/10, col = c(2,4)[df$type])
}
)