[英]Adding a weighted least squares trendline in ggplot2
I am preparing a plot using ggplot2, and I want to add a trendline that is based on a weighted least squares estimation. 我正在使用ggplot2准备一个情节,我想添加一个基于加权最小二乘估计的趋势线。
In base graphics this can be done by sending a WLS model to abline
: 在基本图形中,这可以通过发送WLS模型来abline
:
mod0 <- lm(ds$dMNP~ds$MNP)
mod1 <- lm(ds$dMNP~ds$MNP, weights = ds$Asset)
symbols(ds$dMNP~ds$MNP, circles=ds$r, inches=0.35)
#abline(mod0)
abline(mod1)
in ggplot2 I set the argument weight
in geom_smooth
but nothing changes: 在GGPLOT2我设定的参数weight
在geom_smooth
但没有什么变化:
ggplot(ds, aes(x=MNP, y=dMNP, size=Asset) +
geom_point(shape=21) +
geom_smooth(method = "lm", weight="Asset", color="black", show.legend = FALSE)
this gives me the same plot as 这给了我同样的情节
ggplot(ds, aes(x=MNP, y=dMNP, size=Asset) +
geom_point(shape=21) +
geom_smooth(method = "lm", color="black", show.legend = FALSE)
I'm late, but for posterity and clarity, here is the full solution: 我迟到了,但为了后人和清晰,这里是完整的解决方案:
ggplot(ds, aes(x = MNP, y = dMNP, size = Asset) +
geom_point(shape = 21) +
geom_smooth(method = "lm", mapping = aes(weight = Asset),
color = "black", show.legend = FALSE)
Don't put the weight name in quotes. 不要将重量名称放在引号中。
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