在有缺失值的加权数据上运行速度

Question

我试图对加权数据进行线性回归。

当使用speedlm时，当数据中缺少值时，我会得到一个错误消息。

 library(speedglm)
 sampleData <- data.frame(w = round(runif(12,0,1)),
                          target = rnorm(12,100,50),
                          predictor = c(NA, rnorm(10, 40, 10),NA))

 summary(sampleData)

w target predictor Min. :0.0000 Min. : -3.381 Min. :22.58 1st Qu.:0.0000 1st Qu.: 48.321 1st Qu.:30.45 Median :1.0000 Median : 84.156 Median :37.09 Mean :0.5833 Mean : 92.306 Mean :35.03 3rd Qu.:1.0000 3rd Qu.:119.891 3rd Qu.:41.96 Max. :1.0000 Max. :223.896 Max. :43.48 NA's :2

 #run linear regression without weights
 linearNoWeights <- lm(formula("target~predictor"), data = sampleData)
 speedLinearNoWeights <- speedlm(formula("target~predictor"), data = sampleData)

 #run linear regression with weights
 linearWithWeights <- lm(formula("target~predictor"), data = sampleData, weights =sampleData[,"w"] )
 speedLinearWithWheights <- speedlm(formula("target~predictor"), data = sampleData, weights =sampleData[,"w"] )

基本错误：：交叉项目(x，y)：不符合参数:警告消息: 1:在sqw *X中，较长的对象长度不是较短对象长度的倍数2:在sqw *y中，较长的对象长度不是从:base：：交叉from(x，y)调用的较短对象长度的倍数。

有什么办法不强迫我在运行回归之前修复数据呢？

Answer 1

您应该尝试更改na.action选项。下面是当我将na.action更改为na.exclude/na.omit时能够运行的代码。

library(speedglm)
sampleData <- data.frame(w = round(runif(12,0,1)),
                         target = rnorm(12,100,50),
                         predictor = c(NA, rnorm(10, 40, 10),NA))
summary(sampleData)

linearNoWeights <- lm(formula("target~predictor"), data = sampleData)
speedLinearNoWeights <- speedlm(formula("target~predictor"), data = sampleData)

options(na.action="na.exclude") # or "na.omit"

linearNoWeights <- lm(formula("target~predictor"), data = sampleData)
    speedLinearNoWeights <- speedlm(formula("target~predictor"), data = sampleData)

您可以查看na.omit或na.exclude的文档，以了解何时使用什么。希望这能有所帮助。