gendat_logreg: Generate Data Based on the Logistic Regression Model.

In jeksterslabds/jeksterslabRds: Jekster's Lab Data Science and Statistics

Description

Generates data based on the logistic regression model using the inverse logit link function.

Usage

gendat_logreg(n, beta, rFUN_X = rnorm, ...)

Arguments

n	Sample size.
beta	k \times 1 vector of k regression parameters.
rFUN_X	The distribution function used to generate values of \mathbf{X}. The default value is rnorm for the Gaussian probability density function.
...	Arguments to pass to rFUN_X.

Details

Randomly generates the data matrix \mathbf{X} and the regressand data \mathbf{y}. \mathbf{y}_{n \times 1} is generated from a binomial distribution where p ≤ft( x \right) is equal to \frac{ 1 } { 1 - e^{- ≤ft( \mathbf{X}_{n \times k} \boldsymbol{β}_{n \times 1} \right)} } .

Value

Returns a list with two elements X and y.

• X is the data matrix, that is an n \times k matrix of n observations of k regressors, which includes a regressor whose value is 1 for each observation.

• y n \times 1 vector of observations on the regressand.

Author(s)

Ivan Jacob Agaloos Pesigan

Examples

data <- gendat_logreg(
  n = 100,
  beta = c(.5, .5, .5),
  rFUN_X = rnorm,
  mean = 0,
  sd = 1
)

jeksterslabds/jeksterslabRds documentation built on July 16, 2020, 3:41 p.m.