[R] bnlearn and cpquery

[Marco Scutari]

Dear Ross,

This usually happen because you have parameters with a value of NaN in your
network, because the data you estimate the network from are sparse and you
are using maximum likelihood estimates. You should either 1) use simpler
networks for which you can estimate all conditional distributions from the
data or 2) use posterior estimates for the parameters.

Cheers,
    Marco


On 13 July 2017 at 06:29, Ross Chapman <rosspjchapman at gmail.com> wrote:

> Hi all
>
>
>
> I have built a Bayesian network using discrete data using the bnlearn
> package.
>
>
>
> When I try to run the cpquery function on this data it returns NaN for some
> some cases.
>
>
>
> Running the cpquery in debug mode for such a case (n=10^5, method="lw")
> creates the following output:
>
>
>
> generated a grand total of 1e+05 samples.
>
>   > event has a probability mass of 14982.37 out of NaN (p = NaN).
>
> [1] NaN
>
>
>
>
>
> The cpquery command takes the following structure:
>
>
>
> cpquery(fullFitted,event=(C1_class=="Med"),
>
>         evidence=list(GK_class = "ModHi",
>
>                       GTh_class = "Lo",
>
>                       GU_class = "Lo",
>
>                       El_class = "Hi",
>
>                       E50_class = "Med",
>
>                       E150_class = "Med"
>
>         ) ,
>
>         n=10^5,   method =  "lw", debug=TRUE)
>
>
>
> Similarly, when I try to run the predict method on the same data, it
> returns
> the following warning:
>
>
>
> Warning message:
> In map.prediction(node = node, fitted = object, data = data, n =
> extra.args$n,  :
>   dropping 38073 observations because generated samples are NAs.
>
>
>
>
>
> Could you advise me why these queries are generating NaN values, and how
> they might be resolved.
>
>
>
> The session info is as follows:
>
>
>
> sessionInfo()
> R version 3.4.1 (2017-06-30)
> Platform: x86_64-w64-mingw32/x64 (64-bit)
> Running under: Windows >= 8 x64 (build 9200)
>
> Matrix products: default
>
> locale:
> [1] LC_COLLATE=English_Australia.1252  LC_CTYPE=English_Australia.1252
> LC_MONETARY=English_Australia.1252
> [4] LC_NUMERIC=C                       LC_TIME=English_Australia.1252
>
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base
>
> other attached packages:
> [1] bnlearn_4.2
>
> loaded via a namespace (and not attached):
> [1] compiler_3.4.1 tools_3.4.1
>
>
>
>
>
> Many thanks in advance
>
>
>
> Ross
>
>
>
>
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>
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>



-- 
Marco Scutari, Ph.D.
Lecturer in Statistics, Department of Statistics
University of Oxford, United Kingdom

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