https://github.com/cran/scModels
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Tip revision: ba14d424c697de7a21f22f10407afbab9c5aaf7d authored by Lisa Amrhein on 24 January 2023, 07:20:02 UTC
version 1.0.4
Tip revision: ba14d42
fit_params.Rd
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/par_est_fns.R
\name{fit_params}
\alias{fit_params}
\title{Functions to estimate parameters of probability distributions by fitting the distributions using optim()}
\usage{
fit_params(x, type, optim_control = list(maxit = 1000))
}
\arguments{
\item{x}{Vector containing the discrete observations}

\item{type}{Keyword for the probability distribution the data is to be fitted
against. Possible values are ("pois", "nb", "del", pig", "pb", "pois2", "nb2", "del2", "pig2"
 "pb2", "zipois", "zinb", "zidel", "zipg", zipb", "zipois2", "zinb2", "zidel2", "zipig2", zipb2")}

\item{optim_control}{List of options to override presets in
the optim function; Set to list(maxit = 1000) by default.
For more details, please refer to the 'control' parameter in the
standard 'optim' function in package 'stats'.}
}
\description{
Functions to estimate parameters of probability distributions by fitting the distributions using optim()
}
\examples{
x1 <- rnbinom(100, size = 13, mu = 9)
p1 <- fit_params(x1, "nb")
s <- sample(x = c(0,1), size = 100, replace = TRUE, prob = c(0.3,0.7))
x2 <- s*x1 + (1-s) * rnbinom(100, size = 15, mu = 53)
p2 <- fit_params(x2, "nb2")
}
\keyword{estimation}
\keyword{parameter}
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