计算MCMC算法的标准差。
ar.choice(init, prior, lh = c("none","gev","gpd","pp","os"), ..., psd,
ar = rep(.4, npar), n = 1000, tol = rep(.05, npar))
init : MCMCalgorithm的起始值的数字向量。
prior : 先前的模型。参见函数前.prob,优先权, 先验规范和prior.lognorm.
lh : 似然函数。应为“无”、“gev”、“gpd”、“pp”和“os”之一。
... : 要传递给posterior函数的可选参数。
psd : 缩写建议标准偏差。
ar : 可选。目标接受率-默认isrep(.4,npar)。
n : 可选。模拟马尔可夫链的长度。
tol : 可选。收敛测试的容差。
data(rainfall)
prrain < - prior.quant(shape = c(38.9, 7.1, 47), scale = c(1.5, 6.3,
2.6))
n < - 10000; t0 < - c(43.2, 7.64, 0.32);
s < - ar.choice(init = t0, prior = prrain, lh = "pp", data = rainfall,
thresh = 40, noy = 54, psd = rep(0.01, 3))
##Alec Stephenson choose suited psd = c(2, .2, .07) which is really
##close to values computed by ``ar.choice''