我希望通过boot.ci函数获得多个统计信息的bootstrap置信区间.这是我的MWE. 我有两个统计数据,想要找到这两个统计信息的bootstrap置信区间.但是,boot.ci函数仅为第一个统计量(t1 *)提供引导置
我有两个统计数据,想要找到这两个统计信息的bootstrap置信区间.但是,boot.ci函数仅为第一个统计量(t1 *)提供引导置信区间,但不为第二个统计量(t2 *)提供自举置信区间.
set.seed(12345) df <- rnorm(n=10, mean = 0, sd = 1) Boot.fun <- function(data, idx) { data1 <- sample(data[idx], replace=TRUE) m1 <- mean(data1) sd1 <- sd(data1) out <- cbind(m1, sd1) return(out) } Boot.fun(data = df) library(boot) boot.out <- boot(df, Boot.fun, R = 20) boot.out RDINARY NONPARAMETRIC BOOTSTRAP Call: boot(data = df, statistic = Boot.fun, R = 20) Bootstrap Statistics : original bias std. error t1* -0.4815861 0.3190424 0.2309631 t2* 0.9189246 -0.1998455 0.2499412 boot.ci(boot.out=boot.out, conf = 0.95, type = c("norm", "basic", "perc", "bca")) BOOTSTRAP CONFIDENCE INTERVAL CALCULATIONS Based on 20 bootstrap replicates CALL : boot.ci(boot.out = boot.out, conf = 0.95, type = c("norm", "basic", "perc", "bca")) Intervals : Level Normal Basic 95% (-1.2533, -0.3479 ) (-1.1547, -0.4790 ) Level Percentile BCa 95% (-0.4842, 0.1916 ) (-0.4842, -0.4629 ) Calculations and Intervals on Original Scale Warning : Basic Intervals used Extreme Quantiles Some basic intervals may be unstable Warning : Percentile Intervals used Extreme Quantiles Some percentile intervals may be unstable Warning : BCa Intervals used Extreme Quantiles Some BCa intervals may be unstable Warning messages: 1: In norm.inter(t, (1 + c(conf, -conf))/2) : extreme order statistics used as endpoints 2: In norm.inter(t, alpha) : extreme order statistics used as endpoints 3: In norm.inter(t, adj.alpha) : extreme order statistics used as endpoints引导包(IMO)对于常规使用来说有点笨拙.简短的回答是你需要为boot.ci指定索引(默认值为1),例如boot.ci(boot.out,索引= 2).很长的答案是,一次获得所有引导程序统计信息的引导CI肯定会很方便!
获取指定结果槽的所有CI:
getCI <- function(x,w) { b1 <- boot.ci(x,index=w) ## extract info for all CI types tab <- t(sapply(b1[-(1:3)],function(x) tail(c(x),2))) ## combine with metadata: CI method, index tab <- cbind(w,rownames(tab),as.data.frame(tab)) colnames(tab) <- c("index","method","lwr","upr") tab } ## do it for both parameters do.call(rbind,lapply(1:2,getCI,x=boot.out))
结果(可能不是你想要的,但很容易重塑):
index method lwr upr normal 1 normal -1.2533079 -0.3479490 basic 1 basic -1.1547310 -0.4789996 percent 1 percent -0.4841726 0.1915588 bca 1 bca -0.4841726 -0.4628899 normal1 2 normal 0.6288945 1.6086459 basic1 2 basic 0.5727462 1.4789105 percent1 2 percent 0.3589388 1.2651031 bca1 2 bca 0.6819394 1.2651031
或者,如果您可以一次获得一个引导方法,我在Github上的扫帚包版本具有此功能(我已经提交了拉取请求)
## devtools::install_github("bbolker/broom") library(broom) tidy(boot.out,conf.int=TRUE,conf.method="perc")