generate_data: Generate dummy data with several distributions

In inbo/inlatools: Diagnostic Tools for INLA Models

Generate dummy data with several distributions

Description

All distributions share the same latent variable \eta_{ij} = a + b_i with b_i = N(0, \sigma_r).

Usage

generate_data(
  a = 0,
  sigma_random = 0.5,
  n_random = 20,
  n_replicate = 10,
  nb_size = 1,
  b_size = 5,
  zero_inflation = 0.5
)

Arguments

a	the intercept of the latent variable
sigma_random	The standard error for the random effect \sigma_r.
n_random	the number of random effect levels (groups).
n_replicate	the number of observation per random effect level.
nb_size	the size parameter of the negative binomial distribution. Passed to the size parameter of stats::rnbinom().
b_size	the size parameter of the binomial distribution. Passed to the size parameter of stats::rbinom().
zero_inflation	the probability the the observed value stems for the a point mass in zero.

Details

• The Poisson distribution uses \lambda = e^{\eta_{ij}}.

• The negation binomial distribution uses \mu = e^{\eta_{ij}}.

• The binomial distribution uses \pi_{ij} = e^{\eta_{ij}}/(e^{\eta_{ij}}+ 1).

Value

A data.frame

• ìd the id of the random effect.

• eta the latent variable.

• zero_inflation use the point mass in zero.

• poisson the Poisson distributed variable.

• zipoisson the zero-inflated Poisson distributed variable.

• negbin the negative binomial distributed variable.

• zinegbin the zero-inflated negative binomial distributed variable.

• binom the binomial distributed variable.

See Also

Other utils: plot.dispersion_check(), plot.distribution_check()

Examples

set.seed(20181202)
head(generate_data())

inbo/inlatools documentation built on Oct. 10, 2024, 8:11 a.m.