% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/estimation.R
\name{fit_distribution}
\alias{fit_distribution}
\title{Uncensored Data Parameter Estimation via Maximum Likelihood}
\usage{
fit_distribution(data, distribution, method = "mle", initial = NULL)
}
\arguments{
\item{data}{Numeric vector of observed process observations.}

\item{distribution}{A \code{gpci_dist} object.}

\item{method}{Optimization method (default \code{"mle"}).}

\item{initial}{Named numeric vector or list of initial parameter values. If \code{NULL},
sensible defaults or sample moments are used.}
}
\value{
An updated \code{gpci_dist} object with estimated parameters.
}
\description{
Fits process distribution parameters to observed uncensored numeric data using
Maximum Likelihood Estimation (MLE).
}
\examples{
data_sample <- rnorm(100, mean = 10, sd = 2)
dist_fitted <- fit_distribution(data_sample, dist_normal())
dist_fitted$params
}
