使用具有方法=“rlm”的stat_smooth的ggplot2中的MM鲁棒估计。 [英] MM robust estimation in ggplot2 using stat_smooth with method = "rlm"

问题描述

函数rlm（MASS）允许M和MM估计用于鲁棒回归。我想在ggplot2中绘制MM稳健回归的平滑图，但我认为当在stat_smooth中选择method =rlm时，自动选择的估计方法是M类型。

是否有任何方法通过ggplot2为rlm函数选择MM类型估计技术？

以下是我的代码：

  df < -  data。 （x= c（119,118,144,127,78.8,98.4,108,50,74,30.4，
 50,72,99,155,113,144,102,131,105,127,120,85,153,40.6,133），
y= c（1.56 ，2.17,0.81,1.07,1.12,2.03,0.90,1.48,0.64，
 0.91,0.85,0.41,0.55,2.18,1.49,1.56,0.82,0.93,0.84,1.84，
 0.78,1.15 ，3.85,3.30,0.94））
 
 library（ggplot2）
 library（MASS）
 
 ggplot（df，aes（x = x，y = y） ）+ geom_point（）+ 
 stat_smooth（method =rlm，fullrange = TRUE）+ xlim（0,160）
  

我已经用rlm摘要本身检查了结果，我很确定ggplot2正在使用（默认值？）M估计值。

如何能我使用rlm函数中的MM估计值吗？

$ $ $ $ $ $ $ $ $ $ $ $ $ $ $ rlm（公式，...，method =MM）

非常感谢您！

解决方案

不幸的是， stat_smooth 和 rlm 都有一个方法参数。这使得它有点难：

  ggplot（df，aes（x = x，y = y））+ $ b $ （公式，数据，权重=权重）rlm（公式，
数据，
权重=权重，
方法=MM）b geom_point（）+ 
 stat_smooth ），
 fullrange = TRUE）+ 
 xlim（0,160）
  

The function rlm (MASS) permits both M and MM estimation for robust regression. I would like to plot the smoother from MM robust regression in ggplot2, however I think that when selecting method = "rlm" in stat_smooth, the estimation method automatically chosen is the M type.

Is there any way of selecting the MM type estimation technique for the rlm function through ggplot2?

Here is my code:

df <-  data.frame("x"=c(119,118,144,127,78.8,98.4,108,50,74,30.4,
50,72,99,155,113,144,102,131,105,127,120,85,153,40.6,133),
"y"=c(1.56,2.17,0.81,1.07,1.12,2.03,0.90,1.48,0.64,
0.91,0.85,0.41,0.55,2.18,1.49,1.56,0.82,0.93,0.84,1.84,
0.78,1.15,3.85,3.30,0.94))      

library(ggplot2)
library(MASS)      

ggplot(df,aes(x=x,y=y))+geom_point()+
stat_smooth(method="rlm",fullrange=TRUE)+xlim(0,160)

I have checked the results with the rlm summary itself, and I am pretty sure ggplot2 is using the (default?) M estimation.

How can I use the MM estimation from the rlm function?

rlm(formula, ...,method = "MM")

Many thanks in advance!

解决方案

Unfortunately both stat_smooth and rlm have a method parameter. That makes it a bit harder:

ggplot(df,aes(x=x,y=y)) +
  geom_point() +
  stat_smooth(method=function(formula,data,weights=weight) rlm(formula,
                                                               data,
                                                               weights=weight,
                                                                method="MM"),
              fullrange=TRUE) +
  xlim(0,160)

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