1
我有一些来自R课程的数据。教授正在使用基础图形手动添加每种类型的线。我想用ggplot2
来做。ggplot2与分类变量的lm行
到目前为止,我已经在不同地区创建一个facet
“d情节ggplot
与hunger
scatter plots
和还分别安装了一个模型来的数据。该特定模型具有图中变量x
与变量group/colour
之间的交互项。
我现在想要做的是为每个面板绘制一个模型。我可以通过使用geom_abline
并将slope
和intercept
定义为系数2的总和(因为组的分类变量具有0/1值并且在每个面板中只有一些值乘以1) - 但是这似乎是不容易。
我试过在lm中使用的相同方程stat_smooth
没有运气,我得到一个错误。
理想情况下,我想人们可以把方程式变成stat_smooth
并让ggplot
做所有的工作。一个人会怎么做呢?
download.file("https://sparkpublic.s3.amazonaws.com/dataanalysis/hunger.csv",
"hunger.csv", method = "curl")
hunger <- read.csv("hunger.csv")
hunger <- hunger[hunger$Sex!="Both sexes",]
hunger_small <- hunger[hunger$WHO.region!="WHO Non Members",c(5,6,8)]
q<- qplot(x = Year, y = Numeric, data = hunger_small,
color = WHO.region) + theme(legend.position = "bottom")
q <- q + facet_grid(.~WHO.region)+guides(col=guide_legend(nrow=2))
q
# I could add the standard lm line from stat_smooth, but I dont want that
# q <- q + geom_smooth(method="lm",se=F)
#I want to add the line(s) from the lm fit below, it is really one line per panel
lmRegion <- lm(hunger$Numeric ~ hunger$Year + hunger$WHO.region +
hunger$Year *hunger$WHO.region)
# I also used a loop to do it, as below, but all in one panel
# I am not able to do that
# with facets, I used a function I found to get the colors
ggplotColours <- function(n=6, h=c(0, 360) +15) {
if ((diff(h)%%360) < 1) h[2] <- h[2] - 360/n
hcl(h = (seq(h[1], h[2], length = n)), c = 100, l = 65)
}
n <- length(levels(hunger_small$WHO.region))
q <- qplot(x = Year, y = Numeric, data = hunger_small,
color = WHO.region) + theme(legend.position = "bottom")
q <- q + geom_abline(intercept = lmRegion$coefficients[1],
slope = lmRegion$coefficients[2], color = ggplotColours(n=n)[1])
for (i in 2:n) {
q <- q + geom_abline(intercept = lmRegion$coefficients[1] +
lmRegion$coefficients[1+i], slope = lmRegion$coefficients[2] +
lmRegion$coefficients[7+i], color = ggplotColours(n=n)[i])
}
有一种方法[这里](http://stackoverflow.com/questions/7549694/ggplot2-adding-regression-line-equation-and-r2-on-graph),其可以适应于多面图。 – mnel 2013-02-19 00:56:30
由于某种原因(还没有弄清楚)我无法重现你的例子(第2-n行没有出现在图上)。 *然而*:据我可以告诉天真的方法('geom_smooth(method =“lm”,se = FALSE)')*应该*给你同样的情节,你正在寻找,带有方面... – 2013-02-19 01:55:26