assess_direct: The assess_direct() function

Description Usage Arguments Value Examples

View source: R/assess_direct.R

Description

The assess_direct function is designed to evaluate the prediction accuracy of a Gaussian Graphical model(GGM) comparing with the true graph structure with a known precision matrix.

Usage

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assess_direct(PREC_for_graph, OMEGA_for_graph, p)

Arguments

PREC_for_graph

It is the known precision matrix which is used to assess the estimated precision matrix from GGM.

OMEGA_for_graph

It is the estimated precision matrix from a GGM.

p

It is an integer representing the number of dimension of both the known and estimated precision matrix.

Value

Return the list of assessment results including sensitivity, specificity, NPV(test negative), PPV(test positive), true positive and true negative.

Examples

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prec1 <- matrix(c(0,2,3,1,0,0.5,0,0,0.4),nrow=3,ncol=3)
prec0 <- matrix(c(0,1,2,1,0.5,0.2,0,1,1),nrow=3,ncol=3)

assessresult <- assess_direct(prec1,prec0,p=3)

superOmics/sparsenetgls documentation built on Sept. 11, 2020, 5:49 a.m.