population.est: Estimate population-level partial correlation coefficients

Description Usage Arguments Value References Examples

View source: R/population.est.R

Description

Estimate population-level partial correlation coefficients in time series data. And also return each individual-level coefficients.

Usage

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population.est(Z, alpha = 0.05, lambda = NULL, ind.ci = FALSE)

Arguments

Z

is a n*p*m dimensional array, where m is number of subjects.

alpha

significance level, default value is 0.05.

lambda

a penalty parameter used in lasso of order sqrt(log(p)/n), if NULL, 2*sqrt(log(p)/n) will be used.

ind.ci

a logical indicating whether to compute 1-α confidence interval of each subject, default value is FALSE.

Value

A popEst class object containing two components.

coef a p*p partial correlation coefficients matrix.

ind.est a m-length list, containing estimates for each individuals.

References

Qiu Y. and Zhou X. (2021). Inference on multi-level partial correlations based on multi-subject time series data, Journal of the American Statistical Association, 00, 1-15

Examples

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## Quick example for the individual-level estimates
data(popsimA)
pc = population.est(popsimA)        # estimating partial correlation coefficients

BrainCon documentation built on Sept. 30, 2021, 5:10 p.m.