sim2: Simulated data set 2

In effectFusion: Bayesian Effect Fusion for Categorical Predictors

Description

The simulated data set sim2 illustrates a setting with 4000 observations from a linear regression model. The model has four independent predictors with either 10 or 100 categories and uniform prior class probabilities. The first covariate with 10 categories has three levels with no effects, three levels with effects of size 0.5 and the remaining three levels have effects of size one. The second covariate with 10 categories has 8 levels with no effects and only one level with an effect of size one. The final covariate with 10 categories has only levels without any effect on the outcome. Analogue to the first one, the covariate with 100 categories has 33 levels with no effects, 33 levels with effects of size 0.5 and 33 levels with effects of size 1.

Usage

data(sim2)

Format

A named list containing the following four variables:

y

vector with 4000 observations of a normal response variable

X

matrix with 4 categorical predictors

beta

vector with coefficients used for data generation

types

character vector with types of covariates, 'o' for ordinal and 'n' for nominal covariates

See Also

effectFusion

effectFusion documentation built on Oct. 14, 2021, 1:07 a.m.