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pgam (version 0.4.12)

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

232

Version

0.4.12

License

GPL (>= 2)

Maintainer

Washington Junger

Last Published

January 13th, 2012

Functions in pgam (0.4.12)

AIC.pgam

AIC extraction
pgam.likelihood

Likelihood function to be maximized
deviance.pgam

Deviance extraction
fitted.pgam

Fitted values extraction
fnz

Utility function
pgam.psi2par

Utility function
periodogram

Raw Periodogram
envelope.pgam

Normal plot with simulated envelope of the residuals.
lpnorm

Utility function
link

Utility function
envelope

Generic function for simulated envelope generation.
plot.pgam

Plot of estimated curves
framebuilder

Utility function
logLik.pgam

Loglik extraction
residuals.pgam

Residuals extraction
intensity

Utility function
backfitting

Backfitting algorithm
pgam.par2psi

Utility function
predict.pgam

Prediction
print.summary.pgam

Summary output
pgam.hes2se

Utility function
summary.pgam

Summary output
bkfsmooth

Smoothing of nonparametric terms
f

Utility function
pgam

Poisson-Gamma Additive Models
g

Utility function
print.pgam

Model output
pgam.fit

One-step ahead prediction and variance
aihrio

Sample dataset
elapsedtime

Utility function
tbl2tex

LaTeX table exporter
formparser

Read the model formula and split it into the parametric and nonparametric partitions
pgam.filter

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

Coefficients extraction