[R] bnlearn and cpquery

Ross Chapman rosspjchapman at gmail.com
Fri Jul 14 09:22:40 CEST 2017

Dear Marco,


Thanks for your helpful comments.


Using the posterior estimates seems to have fixed the problem.




From: Marco Scutari [mailto:marco.scutari at gmail.com] 
Sent: Thursday, 13 July 2017 7:35 PM
To: Ross Chapman <rosspjchapman at gmail.com>
Cc: r-help <r-help at r-project.org>
Subject: Re: [R] bnlearn and cpquery



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.





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

Hi all

I have built a Bayesian network using discrete data using the bnlearn

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:


        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:

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

[1] LC_COLLATE=English_Australia.1252  LC_CTYPE=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


        [[alternative HTML version deleted]]

R-help at r-project.org <mailto:R-help at r-project.org>  mailing list -- To UNSUBSCRIBE and more, see
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


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

	[[alternative HTML version deleted]]

More information about the R-help mailing list