问题描述
我正在尝试编写一个 Winbugs/Jags 模型来对多粒度主题模型进行建模(正是这篇论文 -> http://www.ryanmcd.com/papers/mg_lda.pdf)
I am trying to write a Winbugs/Jags model for modeling multi grain topic models (exactly this paper -> 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.例如:我想做类似的事情
Here I would like to choose a different distribution based on a particular value.For Eg: I would like to do something like
`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?
Is this possible to be done in Winbugs/JAGS?
推荐答案
Winbugs/JAGS 不是过程语言,因此您不能使用这样的结构.使用 step
功能.引自手册:
Winbugs/JAGS is not a procedural language, so you cannot use the construct like that. Use step
function. Quote from the manual:
step(e) ...... 1 if e >= 0;0 否则
所以你需要一个技巧来改变条件:
So you need a trick to change the condition:
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
然后将其用于索引技巧:
and then use this for indexing trick:
# 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]]
这篇关于根据 WinBugs/JAGS 中的 if - else 条件选择不同的发行版的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!