poisson_pred: poisson_pred

In kDGLM: Bayesian Analysis of Dynamic Generalized Linear Models

poisson_pred

Description

Calculate the values for the predictive distribution given the values of the parameter of the conjugated distribution of the linear predictor. The data is assumed to have Poisson distribution with its mean having distribution Gamma with shape parameter a e rate parameter b. In this scenario, the marginal distribution of the data is Negative Binomial with a as the dispersion parameter and b/(b+1) as the probability.

Usage

poisson_pred(conj.param, outcome = NULL, parms = list(), pred.cred = 0.95)

Arguments

conj.param	list or data.frame: The parameters of the conjugated distributions of the linear predictor.
outcome	numeric or matrix (optional): The observed values at the current time. Not used in this function.
parms	list (optional): A list of extra parameters for the model. Not used in this function.
pred.cred	numeric: the desired credibility for the credibility interval.

Value

A list containing the following values:

• pred numeric/matrix: the mean of the predictive distribution of a next observation. Same type and shape as the parameter in model.

• var.pred numeric/matrix: the variance of the predictive distribution of a next observation. Same type and shape as the parameter in model.

• icl.pred numeric/matrix: the percentile of 100*((1-pred.cred)/2)

• icu.pred numeric/matrix: the percentile of 100*(1-(1-pred.cred)/2)

• log.like numeric: the The log likelihood for the outcome given the conjugated parameters.

See Also

Other auxiliary functions for a Poisson outcome: convert_Normal_Poisson(), convert_Poisson_Normal(), update_Poisson()

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