fun_rdirichlet_population: Generate a Dirichlet-Dirichlet population.

In lgaborini/rsamplestudy: Easily generate two-level studies from known distributions

Description

Generate samples from m sources and p parameters, n sample per source. Optionally pass the between-source alpha hyperparameter used to generate the source parameters.

Usage

fun_rdirichlet_population(
  n,
  m,
  p,
  alpha = NULL,
  name_var = "x",
  name_source = "theta"
)

Arguments

n	number of samples per source
m	number of sources
p	number of variables
alpha	between-source alpha hyperparameter, a numeric vector or 1-row data.frame. If NULL (default), it is generated from the Uniform distribution on the (p-1)-simplex (see fun_rdirichlet_hyperparameter()).
name_var	names for data variables (default: 'x')
name_source	names for source parameters (default: 'theta')

Value

list of samples:

• alpha: the Dirichlet hyperparameter

• df_sources: tibble of the Dirichlet population parameters, source column is 'source', variables start with name_source

• df_pop: the Dirichlet data, source column is 'source', variables start with name_var

• names_var: names of columns containing data variables

• names_source: names of columns containing source variables

See Also

Other population functions: fun_rnorm_population()

lgaborini/rsamplestudy documentation built on March 6, 2021, 3:18 p.m.