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pgam (version 0.4.5)

Poisson-Gamma Additive Models.

Description

This work is an extension of the state space model for Poisson count data, Poisson-Gamma model, towards a semiparametric specification. Just like the generalized additive models (GAM), cubic splines are used for covariate smoothing. The semiparametric models are fitted by an iterative process that combines maximization of likelihood and backfitting algorithm.

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Version

Install

install.packages('pgam')

Monthly Downloads

246

Version

0.4.5

License

GPL version 2 or later

Maintainer

Washington Junger

Last Published

August 19th, 2022

Functions in pgam (0.4.5)

intensity

Utility function
backfitting

Backfitting algorithm
pgam.filter

Estimation of the conditional distributions parameters of the level
deviance.pgam

Deviance extraction
residuals.pgam

Residuals extraction
formparser

Read the model formula and split it into the parametric and nonparametric partitions
framebuilder

Utility function
elapsedtime

Utility function
fnz

Utility function
logLik.pgam

Loglik extraction
pgam.likelihood

Likelihood function to be maximized
coef.pgam

Coefficients extraction
plot.pgam

Plot of estimated curves
predict.pgam

Prediction
fitted.pgam

Fitted values extraction
print.summary.pgam

Summary output
summary.pgam

Summary output
print.pgam

Model output
g

Utility function
pgam.par2psi

Utility function
link

Utility function
lpnorm

Utility function
AIC.pgam

AIC extraction
tbl2tex

LaTeX table exporter
periodogram

Raw Periodogram
pgam

Poisson-Gamma Additive Models
aihrio

Sample dataset
envelope

Generic function for simulated envelope generation.
bkfsmooth

Smoothing of nonparametric terms
pgam.hes2se

Utility function
pgam.fit

One-step ahead prediction and variance
envelope.pgam

Normal plot with simulated envelope of the residuals.
pgam.psi2par

Utility function
f

Utility function