距离矩阵多重回归的自引导系数（MRM）

Question

我想估计MRM系数的频率分布以产生95％CI。以下是初始代码：

library(ecodist) 
dat=data.frame(matrix(rnorm(3*25),ncol=3)) 
names(dat)<-c('Pred','Var1','Var2') 
mod<-MRM(dist(Pred) ~ dist(Var1) + dist (Var2), data=dat, nperm=100) 
slopes<-mod$coef 

如何自举系数值？

Answer 1

您可以使用boot库中的boot函数。我不知道ecodist::MRM。虽然，这里是一个接近从boot帮助页面展示了如何做到系数估计的非参数引导一个lm模型，并得到偏差和置信区间

> library(boot) 
> nuke <- nuclear[, c(1, 2, 5, 7, 8, 10, 11)] 
> nuke.lm <- lm(log(cost) ~ date+log(cap)+ne+ct+log(cum.n)+pt, data = nuke) 
> 
> nuke.fun <- function(dat, inds, i.pred, fit.pred, x.pred) 
+ { 
+ lm.b <- lm(log(cost) ~ date+log(cap)+ne+ct+log(cum.n)+pt, 
+    data = dat[inds, ]) 
+ coef(lm.b) 
+ } 
> 
> set.seed(45282964) 
> nuke.boot <- boot(nuke, nuke.fun, R = 999) 
> nuke.boot 

ORDINARY NONPARAMETRIC BOOTSTRAP 


Call: 
boot(data = nuke, statistic = nuke.fun, R = 999) 


Bootstrap Statistics : 
     original  bias std. error 
t1* -13.26031434 -0.482810992 4.93147203 
t2* 0.21241460 0.006775883 0.06480161 
t3* 0.72340795 0.001842262 0.14160523 
t4* 0.24902491 -0.004979272 0.08857604 
t5* 0.14039305 0.009209543 0.07253596 
t6* -0.08757642 0.002417516 0.05489876 
t7* -0.22610341 0.006136044 0.12140501 
> 
> boot.ci(nuke.boot, index = 2) # pick the covariate index you want 
BOOTSTRAP CONFIDENCE INTERVAL CALCULATIONS 
Based on 999 bootstrap replicates 

CALL : 
boot.ci(boot.out = nuke.boot, index = 2) 

Intervals : 
Level  Normal    Basic   
95% (0.0786, 0.3326) (0.0518, 0.3215) 

Level  Percentile   BCa   
95% (0.1033, 0.3730) (0.0982, 0.3688) 
Calculations and Intervals on Original Scale 
Warning message: 
In boot.ci(nuke.boot, index = 2) : 
    bootstrap variances needed for studentized intervals 

见戴维森复制粘贴示例，AC和Hinkley，DV （1997）Bootstrap方法及其应用。剑桥大学出版社了解上述输出的细节。你应该考虑你想用bootstrap实现什么，并考虑使用哪种引导程序。