infer.conditional {CRF}

Conditional inference method

Description

Computing the partition function and marginal probabilities

Usage

infer.conditional(crf, clamped, infer.method, ...)

Arguments

crf

The CRF

clamped

The vector of fixed values for clamped nodes, 0 for unfixed nodes

infer.method

The inference method to solve the clamped CRF

...

The parameters for infer.method

Details

Conditional inference (takes another inference method as input)

Value

This function will return a list with components:

node.bel

Node belief. It is a matrix with crf$n.nodes rows and crf$max.state columns.

edge.bel

Edge belief. It is a list of matrices. The size of list is crf$n.edges and the matrix i has crf$n.states[crf$edges[i,1]] rows and crf$n.states[crf$edges[i,2]] columns.

logZ

The logarithmic value of CRF normalization factor Z.

Examples

library(CRF)
data(Small)
i <- infer.conditional(Small$crf, c(0,1,0,0), infer.exact)