% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/lgspline.R
\docType{package}
\name{lgspline-package}
\alias{lgspline-package}
\title{Lagrangian Multiplier Smoothing Splines}
\description{
Implements Lagrangian multiplier smoothing splines for flexible nonparametric regression and function estimation. Provides tools for fitting, prediction, and inference using a constrained optimization approach to enforce smoothness. Supports generalized linear models, Weibull accelerated failure time (AFT) models, quadratic programming constraints, and customizable working-correlation structures, with options for parallel fitting. The core spline construction builds on Ezhov et al. (2018) \doi{10.1515/jag-2017-0029}. Quadratic-programming and SQP details follow Goldfarb & Idnani (1983) \doi{10.1007/BF02591962} and Nocedal & Wright (2006) \doi{10.1007/978-0-387-40065-5}. For smoothing spline and penalized spline background, see Wahba (1990) \doi{10.1137/1.9781611970128} and Wood (2017) \doi{10.1201/9781315370279}. For variance-component and correlation-parameter estimation, see Searle et al. (2006) <ISBN:978-0470009598>. The default multivariate partitioning step uses k-means clustering as in MacQueen (1967).
}
\seealso{
Useful links:
\itemize{
  \item \url{https://github.com/matthewlouisdavisBioStat/lgspline}
  \item Report bugs at \url{https://github.com/matthewlouisdavisBioStat/lgspline/issues}
}

}
\author{
\strong{Maintainer}: Matthew Davis \email{matthewlouisdavis@gmail.com} (\href{https://orcid.org/0000-0001-9714-1018}{ORCID})

}
\keyword{constrained}
\keyword{internal}
\keyword{lagrangian}
\keyword{monomial}
\keyword{multiplier}
\keyword{parametric}
\keyword{regression}
\keyword{smoothing}
