Fitting and Forecasting Gegenbauer ARMA Time Series Models
AIC for model
ggplot of the Forecasts of the model.
Model Coefficients
Extract underlying ARMA process.
Extract fitted values
Forecast future values.
ggtsdisplay of underlying ARMA process.
garma: A package for estimating and foreasting Gegenbauer time series ...
Display raw periodogram
Extract semiparametric estimates of the Gegenbauer factors.
Goodness-of-Fit test for a garma_model.
Log Likelihood
Plot Forecasts from model.
Predict future values.
print a garma_model object.
Print a 'ggbr_factors' object.
Residuals
summarise a garma_model object.
Diagnostic fit of a garma_model.
Covariance matrix
Methods for estimating univariate long memory-seasonal/cyclical Gegenbauer time series processes. See for example (2022) <doi:10.1007/s00362-022-01290-3>. Refer to the vignette for details of fitting these processes.