Poisson: Poisson outcome for kDGLM models

In kDGLM: Bayesian Analysis of Dynamic Generalized Linear Models

Poisson outcome for kDGLM models

Description

Creates an outcome with Poisson distribution with the chosen parameter.

Usage

Poisson(lambda, data, offset = as.matrix(data)^0)

Arguments

lambda	character: The name of the linear predictor associated with the rate (mean) parameter of the Poisson distribution. The parameter is treated as unknown and equal to the exponential of the associated linear predictor.
data	numeric: The values of the observed data.
offset	numeric: The offset at each observation. Must have the same shape as 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(), Multinom(), Normal(), summary.dlm_distr()

Examples

data <- c(AirPassengers)

level <- polynomial_block(rate = 1, D = 0.95, order = 2)
season <- harmonic_block(rate = 1, period = 12, D = 0.975)

outcome <- Poisson(lambda = "rate", data = data)

fitted.data <- fit_model(level, season,
  AirPassengers = outcome
)
summary(fitted.data)

plot(fitted.data, plot.pkg = "base")

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