population.est: Estimate population-level partial correlation coefficients In BrainCon: Inference the Partial Correlations Based on Time Series Data

 population.est R Documentation

Estimate population-level partial correlation coefficients

Description

Estimate population-level partial correlation coefficients in time series data. And also return coefficients for each individual. Input time series data for population as a 3-dimensional array or a list.

Usage

```population.est(
Z,
lambda = NULL,
type = c("slasso", "lasso"),
alpha = 0.05,
ind.ci = FALSE
)
```

Arguments

 `Z` If each individual shares the same number of periods of time, `Z` can be a n*p*m dimensional array, where m is number of individuals. In general, `Z` should be a m-length list, and each element in the list is a n_i*p matrix, where n_i stands for the number of periods of time of the i-th individual. `lambda` a scalar or a m-length vector, representing the penalty parameters of order √{\log(p)/n_i} for each individual. If a scalar, the penalty parameters used in each individual are the same. If a m-length vector, the penalty parameters for each individual are specified in order. And if `NULL`, penalty parameters are specified by `type`. More details about the penalty parameters are in `individual.est`. `type` a character string representing the method of estimation. `"slasso"` means scaled lasso, and `"lasso"` means lasso. Default value is `"slasso"`. `alpha` a numeric scalar, default value is `0.05`. It is used when `ind.ci` is `TRUE`. `ind.ci` a logical indicating whether to compute 1-α confidence intervals 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.

`type` regression type in estimation.

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

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

## Inference on the first subject in population
Res_1 = individual.test(pc\$ind.est[[1]])

```

BrainCon documentation built on April 21, 2022, 5:08 p.m.