% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/start_values.R
\name{start_values}
\alias{start_values}
\title{Generate Initial Values for BARMA Model Estimation}
\usage{
start_values(y, link, ar = integer(0), ma = integer(0), xreg = NA)
}
\arguments{
\item{y}{A numeric time series with values in the open interval (0, 1).}

\item{link}{A string specifying the link function for the mean.}

\item{ar}{A numeric vector of autoregressive (AR) lags. Defaults to
\code{integer(0)}, which omits the AR component entirely.}

\item{ma}{A numeric vector of moving average (MA) lags. Defaults to
\code{integer(0)}, which omits the MA component entirely.}

\item{xreg}{An optional numeric matrix or data frame of exogenous variables.}
}
\value{
A named numeric vector containing the initial values for the model
parameters (`alpha`, `varphi`, `theta`, `beta`, `phi`), ready to be
used by an optimization routine.
}
\description{
This function calculates reasonable starting values for the parameters of
various Beta Autoregressive Moving Average (BARMA) models. The method is
based on the approach proposed by Ferrari & Cribari-Neto (2004) for
beta regression, adapted here for the time series context.
}
\details{
The function computes initial values by fitting a linear model
(`lm.fit`) to the link-transformed response variable `g(y)`.
This provides a computationally cheap and stable way to initialize the
main optimization algorithm.
}
\author{
Original code by Fabio M. Bayer (bayer@ufsm.br).
Substantially modified and improved by Everton da Costa
(everto.cost@gmail.com).
}
