在R中,mean()和median()是标准函数,它们执行您所期望的功能。Mode()告诉您对象的内部存储模式,而不是参数中出现次数最多的值。但是是否存在一个标准库函数来实现向量(或列表)的统计模式?
当前回答
这个黑客应该工作良好。给你的值以及模式的计数:
Mode <- function(x){
a = table(x) # x is a vector
return(a[which.max(a)])
}
其他回答
为了生成模式,我写了下面的代码。
MODE <- function(dataframe){
DF <- as.data.frame(dataframe)
MODE2 <- function(x){
if (is.numeric(x) == FALSE){
df <- as.data.frame(table(x))
df <- df[order(df$Freq), ]
m <- max(df$Freq)
MODE1 <- as.vector(as.character(subset(df, Freq == m)[, 1]))
if (sum(df$Freq)/length(df$Freq)==1){
warning("No Mode: Frequency of all values is 1", call. = FALSE)
}else{
return(MODE1)
}
}else{
df <- as.data.frame(table(x))
df <- df[order(df$Freq), ]
m <- max(df$Freq)
MODE1 <- as.vector(as.numeric(as.character(subset(df, Freq == m)[, 1])))
if (sum(df$Freq)/length(df$Freq)==1){
warning("No Mode: Frequency of all values is 1", call. = FALSE)
}else{
return(MODE1)
}
}
}
return(as.vector(lapply(DF, MODE2)))
}
让我们试试吧:
MODE(mtcars)
MODE(CO2)
MODE(ToothGrowth)
MODE(InsectSprays)
这里有另一个解决方案:
freq <- tapply(mySamples,mySamples,length)
#or freq <- table(mySamples)
as.numeric(names(freq)[which.max(freq)])
下面是一个查找模式的函数:
mode <- function(x) {
unique_val <- unique(x)
counts <- vector()
for (i in 1:length(unique_val)) {
counts[i] <- length(which(x==unique_val[i]))
}
position <- c(which(counts==max(counts)))
if (mean(counts)==max(counts))
mode_x <- 'Mode does not exist'
else
mode_x <- unique_val[position]
return(mode_x)
}
模式并不是在所有情况下都有用。所以函数应该处理这种情况。试试下面的函数。
Mode <- function(v) {
# checking unique numbers in the input
uniqv <- unique(v)
# frquency of most occured value in the input data
m1 <- max(tabulate(match(v, uniqv)))
n <- length(tabulate(match(v, uniqv)))
# if all elements are same
same_val_check <- all(diff(v) == 0)
if(same_val_check == F){
# frquency of second most occured value in the input data
m2 <- sort(tabulate(match(v, uniqv)),partial=n-1)[n-1]
if (m1 != m2) {
# Returning the most repeated value
mode <- uniqv[which.max(tabulate(match(v, uniqv)))]
} else{
mode <- "Two or more values have same frequency. So mode can't be calculated."
}
} else {
# if all elements are same
mode <- unique(v)
}
return(mode)
}
输出,
x1 <- c(1,2,3,3,3,4,5)
Mode(x1)
# [1] 3
x2 <- c(1,2,3,4,5)
Mode(x2)
# [1] "Two or more varibles have same frequency. So mode can't be calculated."
x3 <- c(1,1,2,3,3,4,5)
Mode(x3)
# [1] "Two or more values have same frequency. So mode can't be calculated."
另一个可能的解决方案:
Mode <- function(x) {
if (is.numeric(x)) {
x_table <- table(x)
return(as.numeric(names(x_table)[which.max(x_table)]))
}
}
用法:
set.seed(100)
v <- sample(x = 1:100, size = 1000000, replace = TRUE)
system.time(Mode(v))
输出:
user system elapsed
0.32 0.00 0.31
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