我只是对我的代码有一个简短的问题。我在运行RStudio的虚拟集群上运行的代码与在物理机上运行的代码之间存在一些差异。为了重现ANOVA表，我们必须创建一个R-Markdown文件。我在集群上运行了我的代码。这是我的代码
```{r, message=FALSE, warning=FALSE}
wine <- read.csv("wine.csv")
cultivar <- as.factor( wine[, "Cultivar"])
alcohol <- wine[, "Alcohol"]
alcohol.list <- split(alcohol, cultivar)
alcohol.list
$`1`
[1] 14.23 13.20 13.16 14.37 13.24 14.20 14.39 14.06 14.83 13.86 14.10 14.12 13.75 14.75 14.38 13.63 14.30 13.83 14.19 13.64
[21] 14.06 12.93 13.71 12.85 13.50 13.05 13.39 13.30 13.87 14.02 13.73 13.58 13.68 13.76 13.51 13.48 13.28 13.05 13.07 14.22
[41] 13.56 13.41 13.88 13.24 13.05 14.21 14.38 13.90 14.10 13.94 13.05 13.83 13.82 13.77 13.74 13.56 14.22 13.29 13.72
$`2`
[1] 12.37 12.33 12.64 13.67 12.37 12.17 12.37 13.11 12.37 13.34 12.21 12.29 13.86 13.49 12.99 11.96 11.66 13.03 11.84 12.33
[21] 12.70 12.00 12.72 12.08 13.05 11.84 12.67 12.16 11.65 11.64 12.08 12.08 12.00 12.69 12.29 11.62 12.47 11.81 12.29 12.37
[41] 12.29 12.08 12.60 12.34 11.82 12.51 12.42 12.25 12.72 12.22 11.61 11.46 12.52 11.76 11.41 12.08 11.03 11.82 12.42 12.77
[61] 12.00 11.45 11.56 12.42 13.05 11.87 12.07 12.43 11.79 12.37 12.04
$`3`
[1] 12.86 12.88 12.81 12.70 12.51 12.60 12.25 12.53 13.49 12.84 12.93 13.36 13.52 13.62 12.25 13.16 13.88 12.87 13.32 13.08
[21] 13.50 12.79 13.11 13.23 12.58 13.17 13.84 12.45 14.34 13.48 12.36 13.69 12.85 12.96 13.78 13.73 13.45 12.82 13.58 13.40
[41] 12.20 12.77 14.16 13.71 13.40 13.27 13.17 14.13
oneway <- function(z)
{
ni <- sapply(z, length)
yi_bar <- sapply(z, mean)
s2i <- sapply(z, sd)
Y_bar <- mean(unlist(z))
g <- length(z)
N <-length(unlist(z))
Within_SS = sum((ni-1) * s2i^2)
Between_SS = sum(ni *((yi_bar)-(Y_bar))^2)
DF_Within = (N - g)
DF_Between = (g - 1)
list("WithinSS" = Within_SS, "BetweenSS"= Between_SS, "DFWithin" = DF_Within, "DFBetween" = DF_Between)
}
alcohol.aov <- oneway(alcohol.list)
alcohol.aov
oneway.table <- function(z)
{
Mean_SSW <- z[[1]]/z[[3]]
Mean_SSB <- z[[2]]/z[[4]]
F_value <- (Mean_SSB/Mean_SSW)
P_value <- pf(F_value, DF_Between, DF_Within, lower.tail = FALSE)
anova <- matrix(c( z[[4]], z[[3]], z[[2]], z[[1]], Mean_SSB, Mean_SSW, F_value, NA, P_value, NA), ncol =5)
dimnames(anova) <- list("Group" = c("cultivar", "Residuals"), "ANOVA" = c("DF", "Sum_Sq", "Mean_Sq", "F_value", "P_value"))
printCoefmat(anova, signif.stars = TRUE, has.Pvalue = TRUE, digits = 3, na.print="")
}
oneway.table(alcohol.aov)
我在虚拟集群上所做的代码工作得很好，并且能够重现此ANOVA表：
DF Sum_Sq Mean_Sq F_value P_value
cultivar 2.000 70.795 35.397 135 <2e-16 ***
Residuals 175.000 45.859 0.262
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
但是，当我在本地计算机上运行它时，出现此错误消息：
Error in pf(F_value, DF_Between, DF_Within, lower.tail = FALSE) : object 'DF_Between' not found
我了解我的第二个代码块中找不到我的DF_Between，但是为什么它可以在群集中而不在本地计算机上工作？
也重新运行我的代码，这次将定义添加到变量中
oneway.table <- function(z)
{
g <- length(z)
N <-length(unlist(z))
DF_Within <- (N - g)
DF_Between <- (g - 1)
Mean_SSW <- z[[1]]/z[[3]]
Mean_SSB <- z[[2]]/z[[4]]
F_value <- (Mean_SSB/Mean_SSW)
P_value <- pf(F_value, DF_Between, DF_Within, lower.tail = FALSE)
anova <- matrix(c( z[[4]], z[[3]], z[[2]], z[[1]], Mean_SSB, Mean_SSW, F_value, NA, P_value, NA), ncol =5)
dimnames(anova) <- list("Group" = c("cultivar", "Residuals"), "ANOVA" = c("DF", "Sum_Sq", "Mean_Sq", "F_value", "P_value"))
printCoefmat(anova, signif.stars = TRUE, has.Pvalue = TRUE, digits = 3, na.print="")
}
oneway.table(alcohol.aov)
但是现在，我的输出看起来像这样：
ANOVA
Group DF Sum_Sq Mean_Sq F_value P_value
cultivar 2.000 70.795 35.397 135
Residuals 175.000 45.859 0.262
没有重要等级的星星或任何P_Value，如果有人可以提供帮助，将不胜感激。
这里是无需说明即可解决的方法。
创建可复制的示例：
alcohol.list <- list("1"=c(14.2, 13.2),
"2"=c(12.3, 12.3),
"3"=c(12.8, 12.9))
alcohol.list
您未触及的oneway功能：
oneway <- function(z)
{
ni <- sapply(z, length)
yi_bar <- sapply(z, mean)
s2i <- sapply(z, sd)
Y_bar <- mean(unlist(z))
g <- length(z)
N <-length(unlist(z))
Within_SS = sum((ni-1) * s2i^2)
Between_SS = sum(ni *((yi_bar)-(Y_bar))^2)
DF_Within = (N - g)
DF_Between = (g - 1)
list("WithinSS" = Within_SS, "BetweenSS"= Between_SS, "DFWithin" = DF_Within, "DFBetween" = DF_Between)
}
alcohol.aov <- oneway(alcohol.list)
最后，您的oneway.table和p.value：
oneway.table <- function(z)
{
Mean_SSW <- z$WithinSS/z$DFWithin
Mean_SSB <- z$BetweenSS/z$DFBetween
F_value <- (Mean_SSB/Mean_SSW)
P_value <- pf(F_value, z$DFBetween, z$DFWithin, lower.tail = FALSE)
anova <- matrix(c(z[[4]], z[[3]], z[[2]], z[[1]], Mean_SSB, Mean_SSW, F_value, NA, P_value, NA), ncol =5)
dimnames(anova) <- list("Group" = c("cultivar", "Residuals"), "ANOVA" = c("DF", "Sum_Sq", "Mean_Sq", "F_value", "P_value"))
printCoefmat(anova, signif.stars = TRUE, has.Pvalue = TRUE, digits = 3, na.print="")
}
oneway.table(alcohol.aov)
返回：
DF Sum_Sq Mean_Sq F_value P_value
cultivar 2.000 1.990 0.995 5.91 0.091 .
Residuals 3.000 0.505 0.168
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
在下面的代码中，在DF_Between方法调用之前未创建pf()。实际上，DF_Within也没有创建，并且在该范围中不存在。
这可以工作，例如：
# create DF_Between and DF_Within first and pass in all three as arguments
oneway.table <- function(z, DF_Between, DF_Within){
Mean_SSW <- z[[1]]/z[[3]]
Mean_SSB <- z[[2]]/z[[4]]
F_value <- (Mean_SSB/Mean_SSW)
P_value <- pf(F_value, DF_Between, DF_Within, lower.tail = FALSE)
...
}
这也可以工作：
oneway.table <- function(z){
Mean_SSW <- z[[1]]/z[[3]]
Mean_SSB <- z[[2]]/z[[4]]
F_value <- (Mean_SSB/Mean_SSW)
# provided that z is a list with the two elements
P_value <- pf(F_value, z$DF_Between, z$DF_Within, lower.tail = FALSE)
...
}
这也可以：
oneway.table <- function(z){
Mean_SSW <- z[[1]]/z[[3]]
Mean_SSB <- z[[2]]/z[[4]]
F_value <- (Mean_SSB/Mean_SSW)
# create DF_Between and DF_Within directly in here
g <- length(z)
N <-length(unlist(z))
DF_Within <- (N - g)
DF_Between <- (g - 1)
P_value <- pf(F_value, DF_Between, DF_Within, lower.tail = FALSE)
...
}
选择哪种方式，您只需要了解R使用的词法作用域规则。省去了冗长而繁琐的解释，这就是它的过程：
发生的搜索过程如下：
如果在以下环境中找不到符号的值，函数已定义，然后在父级中继续搜索环境。搜索继续沿父级顺序进行直到我们到达顶层环境为止；这通常是全局环境（工作区）或包的名称空间。后在顶层环境中，搜索将继续在搜索列表中进行直到我们遇到了空旷的环境。
[在您本地计算机的环境中，它首先在定义该功能的环境DF_Between中搜索DF_Within和oneway.table。那里没有找到，所以在父环境中搜索了DF_Between和DF_Within，也没有找到它，并且它到达了空环境。
但是在您的群集上，它首先在定义该功能的环境DF_Between中搜索DF_Within和oneway.table。找不到它，因此在父环境中搜索了DF_Between和DF_Within并找到了它。因此没有引发错误或异常。
您可以通过运行ls()进行打印以确认并确认DF_Within和DF_Between是否存在于群集的父环境中，而不是在本地计算机上。