| % File src/library/stats/man/profile.nls.Rd |
| % Part of the R package, https://www.R-project.org |
| % Copyright 1995-2019 R Core Team |
| % Distributed under GPL 2 or later |
| |
| \name{profile.nls} |
| \alias{profile.nls} |
| \title{Method for Profiling nls Objects} |
| \description{ |
| Investigates the profile log-likelihood function for a fitted model of |
| class \code{"nls"}. |
| } |
| \usage{ |
| \method{profile}{nls}(fitted, which = 1:npar, maxpts = 100, alphamax = 0.01, |
| delta.t = cutoff/5, \dots) |
| } |
| \arguments{ |
| \item{fitted}{the original fitted model object.} |
| \item{which}{the original model parameters which should be profiled. |
| This can be a numeric or character vector. |
| By default, all non-linear parameters are profiled.} |
| \item{maxpts}{maximum number of points to be used for profiling each |
| parameter.} |
| \item{alphamax}{highest significance level allowed |
| for the profile t-statistics.} |
| \item{delta.t}{suggested change on the scale of the profile |
| t-statistics. Default value chosen to allow profiling at about |
| 10 parameter values.} |
| \item{\dots}{further arguments passed to or from other methods.} |
| } |
| \value{ |
| A list with an element for each parameter being profiled. The elements |
| are data-frames with two variables |
| \item{par.vals}{a matrix of parameter values for each fitted model.} |
| \item{tau}{the profile t-statistics.} |
| } |
| \details{ |
| The profile t-statistics is defined as the square root of change in |
| sum-of-squares divided by residual standard error with an |
| appropriate sign. |
| } |
| \references{ |
| Bates, D. M. and Watts, D. G. (1988), \emph{Nonlinear Regression Analysis |
| and Its Applications}, Wiley (chapter 6). |
| } |
| \author{ |
| Of the original version, |
| Douglas M. Bates and Saikat DebRoy |
| } |
| \seealso{ |
| \code{\link{nls}}, \code{\link{profile}}, \code{\link{plot.profile.nls}} |
| } |
| \examples{ |
| \dontshow{od <- options(digits = 4)} |
| # obtain the fitted object |
| fm1 <- nls(demand ~ SSasympOrig(Time, A, lrc), data = BOD) |
| # get the profile for the fitted model: default level is too extreme |
| pr1 <- profile(fm1, alpha = 0.05) |
| # profiled values for the two parameters |
| ## IGNORE_RDIFF_BEGIN |
| pr1$A |
| pr1$lrc |
| ## IGNORE_RDIFF_END |
| # see also example(plot.profile.nls) |
| \dontshow{options(od)} |
| } |
| \keyword{nonlinear} |
| \keyword{regression} |
| \keyword{models} |