Multinom: Multinom outcome for kDGLM models

In kDGLM: Bayesian Analysis of Dynamic Generalized Linear Models

Multinom outcome for kDGLM models

Description

Creates an outcome with Multinomial distribution with the chosen parameters.

Usage

Multinom(p, data, offset = as.matrix(data)^0, base.class = NULL)

Arguments

p	character: a vector with the name of the linear predictor associated with the probability of each category (except the base one, which is assumed to be the last).
data	vector: Values of the observed data.
offset	vector: The offset at each observation. Must have the same shape as data.
base.class	character or integer: The name or index of the base class. Default is to use the last column of data.

Details

For evaluating the posterior parameters, we use the method proposed in \insertCiteArtigokParametrico;textualkDGLM.

For the details about the implementation see \insertCiteArtigoPacote;textualkDGLM.

Value

A object of the class dlm_distr

References

\insertAllCited

See Also

fit_model

Other auxiliary functions for a creating outcomes: Gamma(), Normal(), Poisson(), summary.dlm_distr()

Examples

structure <- (
  polynomial_block(p = 1, order = 2, D = 0.95) +
    harmonic_block(p = 1, period = 12, D = 0.975) +
    noise_block(p = 1, R1 = 0.1) +
    regression_block(p = chickenPox$date >= as.Date("2013-09-01"))
  # Vaccine was introduced in September of 2013
) * 4

outcome <- Multinom(p = structure$pred.names, data = chickenPox[, c(2, 3, 4, 6, 5)])
fitted.data <- fit_model(structure, chickenPox = outcome)
summary(fitted.data)
plot(fitted.data, plot.pkg = "base")

kDGLM documentation built on April 4, 2025, 4:44 a.m.