rmreg: Generate data from a mixture of regression model

In comeetie/greed: Clustering and Model Selection with the Integrated Classification Likelihood

Generate data from a mixture of regression model

Description

rmreg returns an X matrix, a y vector and the cluster labels generated randomly with a Mixture of regression model.

Usage

rmreg(
  N,
  pi,
  A,
  sigma,
  X = cbind(rep(1, N), matrix(stats::rnorm(N * (ncol(A) - 1)), N, ncol(A) - 1))
)

Arguments

N	A numeric value the size of the graph to generate
pi	A numeric vector of length K with clusters proportions (must sum up to 1)
A	A numeric matrix of dim K x d with the regression coefficient
sigma	A numeric of length 1 with the target conditional variance
X	A matrix of covariate

Details

It takes the sample size, cluster proportions and regression parameters matrix and variance as input accordingly

Value

A list with fields:

• X: the covariate matrix

• y: the target feature

• K: number of generated clusters

• N: sample size

• cl: vector of clusters labels

• pi: clusters proportions

• A: regression coefficients used in the simulation

• sigma: conditional variance

comeetie/greed documentation built on Oct. 10, 2022, 5:37 p.m.