Question

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。

我在out中有两个统计信息，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

Answer 1

boot.ci包裹（IMO）对于常规使用来说有点笨拙。简短的回答是，您需要将boot.ci(boot.out,index=2)（默认值为1）指定为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))，例如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。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：

broom

结果（可能不是你想要的，但很容易重塑）：

## devtools::install_github("bbolker/broom")
library(broom)
tidy(boot.out,conf.int=TRUE,conf.method="perc")

或者，如果您可以一次获得一个引导方法，我在Github上的360 degrees = 2 * PI包的版本具有此功能（我已经提交了拉取请求）

...
board.arc(canvas.width/2, canvas.height/2, 10, 0, Math.PI * 2);

通过boot.ci函数获取多个统计信息的Bootstrap Confidence Intervals

1 个答案: