% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/pmm3_ts_main.R
\name{ar_pmm3}
\alias{ar_pmm3}
\title{Fit an AR model using PMM3}
\usage{
ar_pmm3(
  x,
  order = 1,
  max_iter = 100,
  tol = 1e-06,
  adaptive = FALSE,
  step_max = 5,
  include.mean = TRUE,
  initial = NULL,
  na.action = na.fail,
  verbose = FALSE
)
}
\arguments{
\item{x}{Numeric vector of time series data}

\item{order}{Integer: AR order (default 1)}

\item{max_iter}{Integer: maximum NR iterations (default 100)}

\item{tol}{Numeric: convergence tolerance (default 1e-6)}

\item{adaptive}{Logical: re-estimate kappa each iteration (default FALSE)}

\item{step_max}{Numeric: maximum NR step size (default 5.0)}

\item{include.mean}{Logical: include mean term (default TRUE)}

\item{initial}{Optional initial parameter estimates}

\item{na.action}{Function for handling missing values (default na.fail)}

\item{verbose}{Logical: print progress information (default FALSE)}
}
\value{
An S4 object of class \code{ARPMM3}
}
\description{
Estimates autoregressive model parameters using the Polynomial Maximization
Method of order 3 (PMM3). Designed for symmetric platykurtic innovations.
}
\examples{
\donttest{
set.seed(42)
x <- arima.sim(n = 200, list(ar = 0.7),
               innov = runif(200, -sqrt(3), sqrt(3)))
fit <- ar_pmm3(x, order = 1)
coef(fit)
}

}
\seealso{
\code{\link{ar_pmm2}}, \code{\link{ma_pmm3}}, \code{\link{lm_pmm3}}
}
