Alexasandro,

just for your information the catnet package can handle missing data, as
well as perturbed data. it deals with discrete data only which is not a
problem for you.

peter



On Sun, Jun 8, 2014 at 9:27 PM, Alexsandro Cândido de Oliveira Silva <
acos@dpi.inpe.br> wrote:

> Hello,
>
> I am using the bnlearn package in R to handle large amounts of data in
> Bayesian networks. The variables are discrete and have more than 3 million
> observations.
> With bn.fit function I could easily get the conditional probability
> distribution. However, some variables have unobserved values ??(i.e., NA or
> NaN). In some variables, unobserved values ??are almost 1 million. This is
> a lot to just delete them.
>
> In tests, I've got this:
>
>  nw.fit <-bn.fit (nw, date, method = 'bayes')
>>
> Error in check.data (date): the data set contains null / NaN / NA values??.
>
> So, how could I deal with the data and get the conditional probability
> distribution?
> Could someone help me?
>
>
> Regards.
> Alexsandro Cândido de Oliveira Silva
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/
> posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



-- 
Peter Salzman, PhD
Department of Biostatistics and Computational Biology
University of Rochester

	[[alternative HTML version deleted]]

