lm从dlply内部调用抛出"0(非NA)情况"错误[r]

Question

我正在使用dlply()与自定义函数平均lm()的斜率适合包含一些NA值的数据,我得到错误"错误在lm.fit(x,y,偏移=偏移,singular.ok = singular.ok,...):0(非NA)案例"

这个错误只发生在我用两个关键变量调用dlply时 - 用一个变量分隔工作正常.

令人讨厌的是我无法使用简单的数据集重现错误,所以我在问题数据集中发布了问题数据集.

这是代码,尽可能最小化,同时仍然产生错误:

masterData <- read.csv("http://dl.dropbox.com/u/48901983/SOquestionData.csv", na.strings="#N/A")

workingData <- data.frame(sample = masterData$sample,
                      substrate = masterData$substrate,
                      el1 = masterData$elapsedHr1,
                      F1 = masterData$r1 - masterData$rK)

#This function is trivial as written; in reality it takes the average of many slopes
meanSlope <- function(df) {
     lm1 <- lm(df$F1 ~ df$el1, na.action=na.omit) #changing to na.exclude doesn't help
     slope1 <- lm1$coefficients[2]
     meanSlope <- mean(c(slope1)) 
}

lsGOOD <- dlply(workingData, .(sample), meanSlope) #works fine

lsBAD <- dlply(workingData, .(sample, substrate), meanSlope) #throws error

提前感谢您的任何见解.

Answer 1

对于您的几个交叉分类,您缺少协变量:

 with(masterData, table(sample, substrate, r1mis = is.na(r1) ) )
#
snipped the nonmissing reports
, , r1mis = TRUE

      substrate
sample 1 2 3 4 5 6 7 8
    3  0 0 0 0 0 0 0 0
    4  0 0 0 0 0 0 0 0
    5  0 0 0 0 0 0 0 0
    6  0 0 0 0 0 0 0 0
    7  0 0 0 0 0 0 3 3
    8  0 0 0 0 0 0 0 3
    9  0 0 0 0 0 0 0 3
    10 0 0 0 0 0 0 0 3
    11 0 0 0 0 0 0 0 3
    12 0 0 0 0 0 0 0 3
    13 0 0 0 0 0 0 0 3
    14 0 0 0 0 0 0 0 3

这将允许您跳过此特定数据中数据不足的子集:

meanSlope <- function(df) { if ( sum(!is.na(df$el1)) < 2 ) { return(NA) } else {
     lm1 <- lm(df$F1 ~ df$el1, na.action=na.omit) #changing to na.exclude doesn't help
     slope1 <- lm1$coefficients[2]
     meanSlope <- mean(c(slope1)) }
}

虽然它取决于一个特定协变量的缺失.更强大的解决方案是用于try捕获错误并转换为NA.

?try