我知道如何引导矢量的平均值:
library(boot)
samplemean <- function(x, d) {
return(mean(x[d]))
}
results_qsec <- boot(data=mtcars$qsec, statistic = samplemean, R=1000)
但我如何引导加权平均值,考虑到例如值mtcars$qsec
,这些值的权重是mtcars$wt
?
答案 0 :(得分:2)
诀窍是指定weighted.mean
的权重作为...
的{{1}}参数的一部分。在这里,我使用boot
作为权重,并将其作为数据框传递,以匹配j
参数。
你走了:
data =
返回:
samplewmean <- function(d, i, j) {
d <- d[i, ]
w <- j[i, ]
return(weighted.mean(d, w))
}
results_qsec <- boot(data= mtcars[, 7, drop = FALSE],
statistic = samplewmean,
R=10000,
j = mtcars[, 6 , drop = FALSE])
与:比较:
ORDINARY NONPARAMETRIC BOOTSTRAP
Call:
boot(data = mtcars[, 7, drop = FALSE], statistic = samplewmean,
R = 10000, j = mtcars[, 6, drop = FALSE])
Bootstrap Statistics :
original bias std. error
t1* 17.75677 0.0006948823 0.3046888
答案 1 :(得分:1)
这是如何:
samplewmean <- function(data, d) {
return(weighted.mean(x=data[d,1], w=data[d,2]))
}
results_qsec <- boot(data=mtcars[,c(7,6)], statistic = samplewmean, R=1000)