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`@@ -3,7 +3,7 @@ Type: Package`
`3`	`3`	`Title: Fitting and Forecasting Gegenbauer ARMA Time Series Models`
`4`	`4`	`Version: 0.9.12`
`5`	`5`	`Date: 2023-02-18`
`6`		`-Authors@R: person("Richard", "Hunt", email = "maint@huntemail.id.au",`
	`6`	`+Author: person("Richard", "Hunt", email = "maint@huntemail.id.au",`
`7`	`7`	`role = c("aut", "cre"))`
`8`	`8`	`Maintainer: Richard Hunt <maint@huntemail.id.au>`
`9`	`9`	`Description: Methods for estimating univariate long memory-seasonal/cyclical`

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`@@ -594,7 +594,6 @@ predict.garma_model<-function(object,n.ahead=1,max_wgts=length(object$diff_y),gg`
`594`	`594`	`#'`
`595`	`595`	`#' @param object (garma_model) The garma_model from which to predict the values.`
`596`	`596`	`#' @param n.ahead (int) The number of time periods to predict ahead. Default: 1`
`597`		`-#' @param ... Other parameters. Ignored.`
`598`	`597`	`#' @return A "ts" object containing the requested forecasts.`
`599`	`598`	`#' @examples`
`600`	`599`	`#' data(AirPassengers)`

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