Fitting and Forecasting Gegenbauer ARMA Time Series Models

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Documentation for package ‘garma’ version 0.9.20

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

garma-package	garma: A package for estimating and foreasting Gegenbauer time series models.
AIC.garma_model	AIC for model
autoplot.garma_model	ggplot of the Forecasts of the model.
coef.garma_model	Model Coefficients
extract_arma	Extract underlying ARMA process.
fitted.garma_model	Extract fitted values
forecast.garma_model	Forecast future values.
garma	garma: A package for estimating and foreasting Gegenbauer time series models.
garma_ggtsdisplay	ggtsdisplay of underlying ARMA process.
ggbr_semipara	Extract semiparametric estimates of the Gegenbauer factors.
gg_raw_pgram	Display raw periodogram
gof	Goodness-of-Fit test for a garma_model.
logLik.garma_model	Log Likelihood
plot.garma_model	Plot Forecasts from model.
predict.garma_model	Predict future values.
print.garma_model	print a garma_model object.
print.ggbr_factors	Print a 'ggbr_factors' object.
residuals.garma_model	Residuals
summary.garma_model	summarise a garma_model object.
tsdiag.garma_model	Diagnostic fit of a garma_model.
vcov.garma_model	Covariance matrix