saeSim (version 0.12.0)

sim_base_lm: 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()