start_matrix: Setup of the start matrix

In RepeatedHighDim: Methods for High-Dimensional Repeated Measures Data

Setup of the start matrix

Description

Generation of the start matrix with n rows and specified marginal probabilities p.

Usage

start_matrix(p, k)

Arguments

p	Marginal probabilities of the start matrix.
k	Number of rows to be generated.

Details

The start matrix needs to be setup for further use in the genetic algorithm implemented in the function iter_matrix. For high-dimensional cases or if the marginal probabilities have multiple decimal places, the number k of rows should be large (up to multiple thousand).

Value

A (k x p)-Matrix with with entries 0 and 1 according to the specified marginal probabilities p.

Author(s)

Jochen Kruppa, Klaus Jung

References

Kruppa, J., Lepenies, B., & Jung, K. (2018). A genetic algorithm for simulating correlated binary data from biomedical research. Computers in biology and medicine, 92, 1-8. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.compbiomed.2017.10.023")}

See Also

For more information, please refer to the package's documentation and the tutorial: https://software.klausjung-lab.de/.

Examples

X0 <- start_matrix(p = c(0.5, 0.6), k = 10000)

## check if p can be restored
apply(X0, 2, mean)

RepeatedHighDim documentation built on April 15, 2025, 1:28 a.m.