Question

我想估计MRM系数的频率分布以生成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

如何引导系数值？

Answer 1

您可以使用ecodist::MRM库中的boot功能。我不知道lm。虽然，这里是> 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帮助页面中的复制粘贴示例，它显示了如何对FrameFormatter[InEvent]模型进行系数估计的非参数自举，并获得偏差和置信区间

FrameFormatter[OutEvent]

见 Davison，A.C。和Hinkley，D.V。（1997）Bootstrap方法及其应用。剑桥大学出版社了解上述输出的详情。您应该考虑使用引导程序实现的目标，并考虑使用哪个引导程序。

距离矩阵（MRM）多元回归的自举系数

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