glarma v1.6-0

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Generalized Linear Autoregressive Moving Average Models

Functions are provided for estimation, testing, diagnostic checking and forecasting of generalized linear autoregressive moving average (GLARMA) models for discrete valued time series with regression variables. These are a class of observation driven non-linear non-Gaussian state space models. The state vector consists of a linear regression component plus an observation driven component consisting of an autoregressive-moving average (ARMA) filter of past predictive residuals. Currently three distributions (Poisson, negative binomial and binomial) can be used for the response series. Three options (Pearson, score-type and unscaled) for the residuals in the observation driven component are available. Estimation is via maximum likelihood (conditional on initializing values for the ARMA process) optimized using Fisher scoring or Newton Raphson iterative methods. Likelihood ratio and Wald tests for the observation driven component allow testing for serial dependence in generalized linear model settings. Graphical diagnostics including model fits, autocorrelation functions and probability integral transform residuals are included in the package. Several standard data sets are included in the package.

Functions in glarma

 Name Description fitted.glarma Extract GLARMA Model Fitted Values residuals.glarma Extract GLARMA Model Residuals paramGen Parameter Generators coef.glarma Extract GLARMA Model Coefficients extractAIC.glarma Extract AIC from a GLARMA Model glarma Generalized Linear Autoregressive Moving Average Models with Various Distributions initial Initial Parameter Generator for GLARMA from GLM summary.glarma Summarize GLARMA Fit PIT Non-randomized Probability Integral Transformation model.frame.glarma Extracting the Model Frame of the GLARMA Model mySolve Matrix Inversion of the Hessian of the Log-Likelihood OxBoatRace Oxford-Cambridge Boat Race Asthma Daily Presentations of Asthma at Campbelltown Hospital nobs.glarma Extract the Number of Observations from a GLARMA Model Fit forecast Forecasting GLARMA time series DriverDeaths Single Vehicle Nighttime Driver Deaths in Utah plotPIT PIT Plots for a glarma Object plot.glarma Plot Diagnostics for a glarma Object Polio Cases of Poliomyelitis in the U.S. RobberyConvict Court Convictions for Armed Robbery in New South Wales logLik.glarma Extract Log-Likelihood from GLARMA Models likTests Likelihood Ratio Test and Wald Test for GLARMA Fit normRandPIT Random normal probability integral transformation No Results!