是否可以在 WinBUGS 中设置种子来重现参数估计，就像在 R 中使用 set.seed 所做的那样？
最佳答案
下面的代码建议您通过在每次运行 WinBUGS 模型之前设置种子，通过 R 重现 WinBUGS 中的估计值。
前四个模型运行紧接着相同的 set.seed 语句。最后两个模型运行则不然。根据 all.equal 语句，前四个模型运行返回相同的估计值。最后两个模型运行没有。
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library(R2WinBUGS)
n <- 15
x <- 1:15
y <- c(32.46, 38.38, 40.92, 22.27, 34.64, 33.53, 26.62, 25.26, 23.67, 20.54, 21.11, 17.00, 16.61, 19.32, 22.29)
print(summary(lm(y ~ x)))
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set.seed(1234)
sink("linreg.txt")
cat("
model {
# Priors
alpha ~ dnorm(0,0.001)
beta ~ dnorm(0,0.001)
sigma ~ dunif(0, 100)
tau <- 1/ (sigma * sigma)
# Likelihood
for (i in 1:n) {
y[i] ~ dnorm(mu[i], tau)
mu[i] <- alpha + beta*x[i]
}
}
",fill=TRUE)
sink()
win.data <- list("x","y", "n")
inits <- function(){list(alpha=rnorm(1), beta=rnorm(1), sigma = rlnorm(1))}
params <- c("alpha", "beta", "sigma")
nc = 2
ni = 1000
nb = 500
nt = 5
out1 <- bugs(data = win.data, inits = inits, parameters = params,
model = "linreg.txt", bugs.directory="c:/WinBUGS14/",
n.thin = nt, n.chains = nc, n.burnin = nb, n.iter = ni)
print(out1, dig = 4)
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set.seed(1234)
sink("linreg.txt")
cat("
model {
# Priors
alpha ~ dnorm(0,0.001)
beta ~ dnorm(0,0.001)
sigma ~ dunif(0, 100)
tau <- 1/ (sigma * sigma)
# Likelihood
for (i in 1:n) {
y[i] ~ dnorm(mu[i], tau)
mu[i] <- alpha + beta*x[i]
}
}
",fill=TRUE)
sink()
win.data <- list("x","y", "n")
inits <- function(){list(alpha=rnorm(1), beta=rnorm(1), sigma = rlnorm(1))}
params <- c("alpha", "beta", "sigma")
nc = 2
ni = 1000
nb = 500
nt = 5
out2 <- bugs(data = win.data, inits = inits, parameters = params,
model = "linreg.txt", bugs.directory="c:/WinBUGS14/",
n.thin = nt, n.chains = nc, n.burnin = nb, n.iter = ni)
print(out2, dig = 4)
####################################################################################
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set.seed(1234)
sink("linreg.txt")
cat("
model {
# Priors
alpha ~ dnorm(0,0.001)
beta ~ dnorm(0,0.001)
sigma ~ dunif(0, 100)
tau <- 1/ (sigma * sigma)
# Likelihood
for (i in 1:n) {
y[i] ~ dnorm(mu[i], tau)
mu[i] <- alpha + beta*x[i]
}
}
",fill=TRUE)
sink()
win.data <- list("x","y", "n")
inits <- function(){list(alpha=rnorm(1), beta=rnorm(1), sigma = rlnorm(1))}
params <- c("alpha", "beta", "sigma")
nc = 2
ni = 1000
nb = 500
nt = 5
out3 <- bugs(data = win.data, inits = inits, parameters = params,
model = "linreg.txt", bugs.directory="c:/WinBUGS14/",
n.thin = nt, n.chains = nc, n.burnin = nb, n.iter = ni)
print(out3, dig = 4)
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set.seed(1234)
sink("linreg.txt")
cat("
model {
# Priors
alpha ~ dnorm(0,0.001)
beta ~ dnorm(0,0.001)
sigma ~ dunif(0, 100)
tau <- 1/ (sigma * sigma)
# Likelihood
for (i in 1:n) {
y[i] ~ dnorm(mu[i], tau)
mu[i] <- alpha + beta*x[i]
}
}
",fill=TRUE)
sink()
win.data <- list("x","y", "n")
inits <- function(){list(alpha=rnorm(1), beta=rnorm(1), sigma = rlnorm(1))}
params <- c("alpha", "beta", "sigma")
nc = 2
ni = 1000
nb = 500
nt = 5
out4 <- bugs(data = win.data, inits = inits, parameters = params,
model = "linreg.txt", bugs.directory="c:/WinBUGS14/",
n.thin = nt, n.chains = nc, n.burnin = nb, n.iter = ni)
print(out4, dig = 4)
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sink("linreg.txt")
cat("
model {
# Priors
alpha ~ dnorm(0,0.001)
beta ~ dnorm(0,0.001)
sigma ~ dunif(0, 100)
tau <- 1/ (sigma * sigma)
# Likelihood
for (i in 1:n) {
y[i] ~ dnorm(mu[i], tau)
mu[i] <- alpha + beta*x[i]
}
}
",fill=TRUE)
sink()
win.data <- list("x","y", "n")
inits <- function(){list(alpha=rnorm(1), beta=rnorm(1), sigma = rlnorm(1))}
params <- c("alpha", "beta", "sigma")
nc = 2
ni = 1000
nb = 500
nt = 5
out5 <- bugs(data = win.data, inits = inits, parameters = params,
model = "linreg.txt", bugs.directory="c:/WinBUGS14/",
n.thin = nt, n.chains = nc, n.burnin = nb, n.iter = ni)
print(out5, dig = 4)
####################################################################################
####################################################################################
sink("linreg.txt")
cat("
model {
# Priors
alpha ~ dnorm(0,0.001)
beta ~ dnorm(0,0.001)
sigma ~ dunif(0, 100)
tau <- 1/ (sigma * sigma)
# Likelihood
for (i in 1:n) {
y[i] ~ dnorm(mu[i], tau)
mu[i] <- alpha + beta*x[i]
}
}
",fill=TRUE)
sink()
win.data <- list("x","y", "n")
inits <- function(){list(alpha=rnorm(1), beta=rnorm(1), sigma = rlnorm(1))}
params <- c("alpha", "beta", "sigma")
nc = 2
ni = 1000
nb = 500
nt = 5
out6 <- bugs(data = win.data, inits = inits, parameters = params,
model = "linreg.txt", bugs.directory="c:/WinBUGS14/",
n.thin = nt, n.chains = nc, n.burnin = nb, n.iter = ni)
print(out6, dig = 4)
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all.equal(out1, out2)
all.equal(out1, out3)
all.equal(out1, out4)
all.equal(out1, out5)
all.equal(out1, out6)
关于r - 通过 R 在 WinBUGS 中设置种子，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/29518877/