GGMncv (version 2.1.1)

confirm_edges: Confirm Edges

Description

Confirmatory hypothesis testing of edges that were initially detected with data-driven model selection.

Usage

confirm_edges(object, Rnew, method, alpha)

Arguments

object

An object of class ggmncv

Rnew

Matrix. A correlation matrix of dimensions p by p.

method

Character string. A correction method for multiple comparison (defaults to fdr). Can be abbreviated. See p.adjust.

alpha

Numeric. Significance level (defaults to 0.05).

Value

An object of class ggmncv, including:

• P: Matrix of confirmed edges (partial correlations)

• adj: Matrix of confirmed edges (adjacency)

Details

The basic idea is to merge exploration with confirmation @see for example, @rodriguez_williams_rast_mulder_2020GGMncv. This is accomplished by testing those edges (in an independent dataset) that were initially detected via data driven model selection.

Confirmatory hypothesis testing follows the approach described in jankova2015confidence;textualGGMncv: (1) graphical lasso is computed with lambda fixed to = log(p)/n, (2) the de-sparsified estimator is computed, and then (3) p-values are obtained for the de-sparsified estimator.

References

Examples

# NOT RUN {
Y <- na.omit(bfi[,1:25])

Y_explore <- Y[1:1000,]

Y_confirm <- Y[1001:nrow(Y),]

fit <- ggmncv(cor(Y_explore),
              n = nrow(Y_explore),
              progress = FALSE)

confirm <- confirm_edges(fit,
                         Rnew = cor(Y_confirm),
                         method = "fdr",
                         alpha = 0.05)
# }