Rstanでワイブル分布のパラメータ推定をしてみる。打切りを考慮するにはどうしたら良いのだろうか？
Stan Modeling Language User’s Guide and Reference Manual, v2.5.0の83ページ辺りを読めば出来そう。
weibull.stan
data {
int<lower=0> J; // number of data
real<lower=0> tt[J]; // time
}
parameters {
real<lower=0> m;
real<lower=0> eta;
}
model {
for(j in 1:J)
tt[j] ~ weibull(m, eta);
}weibull.R
library(rstan)
data.ls <- list(J = 1000,
tt = rweibull(1000, shape = 2, scale = 100))
fit <- stan(file = 'weibull.stan', data = data.ls,
iter = 1000, chains = 4)結果
> fit
Inference for Stan model: weibull.
4 chains, each with iter=1000; warmup=500; thin=1;
post-warmup draws per chain=500, total post-warmup draws=2000.
mean se_mean sd 2.5% 25% 50% 75% 97.5% n_eff Rhat
m 2.02 0.00 0.05 1.93 1.99 2.02 2.05 2.12 946 1
eta 101.42 0.05 1.67 98.32 100.24 101.39 102.60 104.82 1007 1
lp__ -5197.22 0.04 0.97 -5199.81 -5197.58 -5196.91 -5196.55 -5196.28 735 1
Samples were drawn using NUTS(diag_e) at Wed Dec 03 23:23:05 2014.
For each parameter, n_eff is a crude measure of effective sample size,
and Rhat is the potential scale reduction factor on split chains (at
convergence, Rhat=1).