data_generator: Data Generator

Description Usage Arguments Value Examples

View source: R/data_generator.R

Description

This functions generates two n by p size samples of multivariate normal data. In doing this it also determines and provides the relevant covariance matrices.

Usage

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data_generator(n, p, Delta = NULL, case = "sparse", seed = NULL)

Arguments

n

The number of observations generated.

p

The number of dimensions for the generated samples.

Delta

Optional parameter - Provides the differential network that will be used to obtain the sample covariance matrices.

case

Optional parameter - Selects under which case the covariance matrices are determined. Possible cases are: "sparse" - Sparse Case or "asymsparse"- Asymptotically Sparse Case. Defaults to "sparse".

seed

Optional parameter - Allows a seed to be set for reproducibility.

Value

A list of various outputs, namely:

Examples

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data <- data_generator(n = 100, p = 50, seed = 123)
data <- data_generator(n = 10, p = 50, case = "asymsparse")

dineR documentation built on Nov. 15, 2021, 5:09 p.m.