我使用自举来获得Weibull分布的置信区间。然后我在情节中绘制了信心带。
代码如下:
set.seed(123)
rw.small<-rweibull(100,shape=1.781096,scale=33.669511)
xs <- seq(0,100, len=500)
boot.pdf <- sapply(1:100, function(i) {
xi <- sample(rw.small, size=length(rw.small), replace=TRUE)
MLE.est <- suppressWarnings(fitdist(xi, distr="weibull",lower=0))
dweibull(xs, shape=MLE.est$estimate["shape"], scale = MLE.est$estimate["scale"])
})
par(bg="white",las=1,cex=1.2)
plot(xs, boot.pdf[, 1], type="l", col=rgb(.6, .6, .6, .1), ylim=range(boot.pdf),
xlab="Note Life (months)", ylab="Probability density",main= "Probability Distribution")
for(i in 2:ncol(boot.pdf)) lines(xs, boot.pdf[, i], col=rgb(.6, .6, .6, .1))
quants <- apply(boot.pdf, 1, quantile, c(0.025, 0.5, 0.975))
min.point <- apply(boot.pdf, 1, min, na.rm=TRUE)
max.point <- apply(boot.pdf, 1, max, na.rm=TRUE)
lines(xs, quants[1, ], col="red", lwd=1.5, lty=2)
lines(xs, quants[3, ], col="red", lwd=1.5, lty=2)
lines(xs, quants[2, ], col="darkred", lwd=2)
两个问题: 1.如何从绘制的置信区间的下限和上限(即两条红线)获得形状和比例参数值?
lines(xs, quants[1, ], col="red", lwd=1.5, lty=2)
lines(xs, quants[3, ], col="red", lwd=1.5, lty=2)
答案 0 :(得分:1)
我不确定问题1。
以下是问题2的一些代码。
library (fitdistrplus) #you forgot to mention this
library (ggplot2)
library (tidyr)
dat <- gather(as.data.frame(boot.pdf), i, y, -1)
dat2 <- gather(as.data.frame(t(quants)), quantile, y)
dat$x <- dat2$x <- xs
ggplot(dat, aes(x, y, group = i)) +
geom_line(col = 'grey') +
geom_line(data = dat2, aes(group = quantile, col = quantile), size = 1) +
scale_color_manual(values = c('2.5%' = 'red', '50%' = 'darkred', '97.5%' = 'red')) +
theme_bw() + xlab("Note Life (months)") + ylab("Probability density") +
ggtitle("Probability Distribution")