components_gather | R Documentation |
Compile conditional probability tables / cliques potentials as a preprocessing step for creating a graphical independence network
compile_cpt(x, ..., forceCheck = TRUE)
compile_pot(x, ..., forceCheck = TRUE)
parse_cpt(xi)
x |
To |
... |
Additional arguments; currently not used. |
forceCheck |
Controls if consistency checks of the probability tables should be made. |
xi |
cpt in some representation |
* `compileCPT` is relevant for turning a collection of cptable's into an object from which a network can be built. For example, when specification of a cpt is made with cptable then the levels of the node is given but not the levels of the parents. `compileCPT` checks that the levels of variables in the cpt's are consistent and also that the specifications define a dag. * `compilePOT` is not of direct relevance for the user for the moment. However, the elements of the input should be arrays which define a chordal undirected graph and the arrays should, if multiplied, form a valid probability density.
A list with a class attribute.
Søren Højsgaard, sorenh@math.aau.dk
Søren Højsgaard (2012). Graphical Independence Networks with the gRain Package for R. Journal of Statistical Software, 46(10), 1-26. https://www.jstatsoft.org/v46/i10/.
extract_cpt
, extract_pot
, extract_marg
example("example_chest_cpt")
x <- compile_cpt(chest_cpt)
class(x)
grain(x)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.