GGMncv (version 2.1.1)

inference: Statistical Inference for Regularized Gaussian Graphical Models

Description

Compute p-values for each relation based on the de-sparsified glasso estimator jankova2015confidenceGGMncv.

Usage

inference(object, method = "fdr", alpha = 0.05, ...)
significance_test(object, method = "fdr", alpha = 0.05, ...)

Arguments

object

An object of class ggmncv

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).

...

Currently ignored.

Value

• Theta De-sparsified precision matrix

• adj Adjacency matrix based on the p-values.

• pval_uncorrected Uncorrected p-values

• pval_corrected Corrected p-values

• method The approach used for multiple comparisons

• alpha Significance level

References

Examples

# NOT RUN {
# data
Y <- GGMncv::ptsd[,1:5]

# fit model
fit <- ggmncv(cor(Y), n = nrow(Y),
              progress = FALSE,
              penalty = "lasso")


# statistical inference
inference(fit)

# alias
all.equal(inference(fit), significance_test(fit))

# }