基于WinBugs / JAGS中的if - else条件选择不同的分布

时间:2013-03-14 16:04:40

标签: if-statement model distribution winbugs jags

我正在尝试编写一个Winbugs / Jags模型来建模多粒度主题模型(正是本文 - > http://www.ryanmcd.com/papers/mg_lda.pdf

在这里,我想根据特定值选择不同的分布。 对于Eg:我想做类似

的事情
`if ( X[i] > 0.5 )
{
Z[i] ~ dcat(theta-gl[D[i], 1:K-gl])
W[i] ~ dcat(phi-gl[z[i], 1:V])
}
else 
{
Z[i] ~ dcat(theta-loc[D[i], 1:K-loc])
W[i] ~ dcat(phi-loc[z[i], 1:V])
}
`

这可以在Winbugs / JAGS中完成吗?

1 个答案:

答案 0 :(得分:8)

Winbugs / JAGS不是一种过程语言,所以你不能使用这样的结构。使用step功能。从手册中引用:

  

步骤(e)...... 1如果e> = 0; 0否则

所以你需要一个技巧来改变条件:

X[i] > 0.5   <=>     
X[i] - 0.5 > 0  <=> 
!(X[i] - 0.5 <= 0) <=>
!(-(X[i] - 0.5) >= 0) <=>
!(step(-(X[i] - 0.5)) == 1) <=>
step(-(X[i] - 0.5)) == 0

然后用它来编制索引技巧:

# then branch
Z_branch[i, 1] ~ dcat(theta-gl[D[i], 1:K-gl])
W_branch[i, 1] ~ dcat(phi-gl[z[i], 1:V])

# else branch
Z_branch[i, 2] ~ dcat(theta-loc[D[i], 1:K-loc])
W_branch[i, 2] ~ dcat(phi-loc[z[i], 1:V])

# decision here
if_branch[i] <- 1 + step(-(X[i] - 0.5)) # 1 for "then" branch, 2 for "else" branch
Z[i] ~ Z_branch[i, if_branch[i]]
W[i] ~ W_branch[i, if_branch[i]]