sim_model: Simulate databases based in models

In ErickChacon/day2day: Functions for Day-to-Day Data Analysis

Description

sim_model simulate a database based on common models. The structure used to create the data is similar as the bamlss.formula.

Usage

sim_model(formula = list(mean ~ 1 + 2 * x1, sd ~ 1), generator = rnorm,
  n = 1000, init_data = NULL, seed = NULL, extent = 1)

Arguments

formula	List of the parameters, indicating how they should be computed. similar to formula for lm, glm, bamlss, with the difference that it included the coefficients and link function explicitly.
generator	Function to generate the response variables given the parameters
n	Number of observations to be simulated
init_data	Initial data including some variables to not been simulated.
seed	Seed to be defined with function set.seed to obtain reproducible results
extent	Spatial extent for the simulation of coordinates when a spatial effect is included.

Value

a tibble containing the simulated predictors, parameters and response variable

Author(s)

Erick Albacharro Chacon-Montalvan

Examples

f <- list(
 mean ~ 5 + 0.5 * x1 + 0.1 * x2 + 0.7 * id1,
 sd ~ exp(x1)
)
data <- sim_model(f, rnorm, 100)

ErickChacon/day2day documentation built on May 6, 2019, 4:03 p.m.