sim_base_lm {saeSim}

Preconfigured set-ups

Description

sim_base_lm() will start a linear model: One regressor, one error component. sim_base_lmm() will start a linear mixed model: One regressor, one error component and one random effect for the domain. sim_base_lmc() and sim_base_lmmc() add outlier contamination to the scenarios. Use these as a quick start, then you probably want to configure your own scenario.

Usage

sim_base_lm()

sim_base_lmm()

sim_base_lmc()

sim_base_lmmc()

Details

Additional information on the generated variables:

• nDomains: 100 domains

• nUnits: 100 in each domain

• x: is normally distributed with mean of 0 and sd of 4

• e: is normally distributed with mean of 0 and sd of 4

• v: is normally distributed with mean of 0 and sd of 1, it is a constant within domains

• e-cont: as e; probability of unit to be contaminated is 0.05; sd is then 150

• v-cont: as v; probability of area to be contaminated is 0.05; sd is then 40

• y = 100 + x + v + e

Examples

# The preconfigured set-ups:
sim_base_lm()
sim_base_lmm()
sim_base_lmc()
sim_base_lmmc()