% File src/library/stats/man/SSasymp.Rd % Part of the R package, https://www.R-project.org % Copyright 1995-2017 R Core Team % Distributed under GPL 2 or later \name{SSasymp} \encoding{UTF-8} \title{Self-Starting \code{nls} Asymptotic Model} \usage{ SSasymp(input, Asym, R0, lrc) } \alias{SSasymp} \arguments{ \item{input}{a numeric vector of values at which to evaluate the model.} \item{Asym}{a numeric parameter representing the horizontal asymptote on the right side (very large values of \code{input}).} \item{R0}{a numeric parameter representing the response when \code{input} is zero.} \item{lrc}{a numeric parameter representing the natural logarithm of the rate constant.} } \description{ This \code{selfStart} model evaluates the asymptotic regression function and its gradient. It has an \code{initial} attribute that will evaluate initial estimates of the parameters \code{Asym}, \code{R0}, and \code{lrc} for a given set of data. Note that \code{\link{SSweibull}()} generalizes this asymptotic model with an extra parameter. } \value{ a numeric vector of the same length as \code{input}. It is the value of the expression \code{Asym+(R0-Asym)*exp(-exp(lrc)*input)}. If all of the arguments \code{Asym}, \code{R0}, and \code{lrc} are names of objects, the gradient matrix with respect to these names is attached as an attribute named \code{gradient}. } \author{\enc{José}{Jose} Pinheiro and Douglas Bates} \seealso{ \code{\link{nls}}, \code{\link{selfStart}} } \examples{ \dontshow{options(show.nls.convergence=FALSE)} Lob.329 <- Loblolly[ Loblolly$Seed == "329", ] SSasymp( Lob.329$age, 100, -8.5, -3.2 ) # response only local({ Asym <- 100 ; resp0 <- -8.5 ; lrc <- -3.2 SSasymp( Lob.329$age, Asym, resp0, lrc) # response _and_ gradient }) getInitial(height ~ SSasymp( age, Asym, resp0, lrc), data = Lob.329) ## Initial values are in fact the converged values fm1 <- nls(height ~ SSasymp( age, Asym, resp0, lrc), data = Lob.329) summary(fm1) ## Visualize the SSasymp() model parametrization : xx <- seq(-.3, 5, length.out = 101) ## Asym + (R0-Asym) * exp(-exp(lrc)* x) : yy <- 5 - 4 * exp(-xx / exp(3/4)) stopifnot( all.equal(yy, SSasymp(xx, Asym = 5, R0 = 1, lrc = -3/4)) ) require(graphics) op <- par(mar = c(0, .2, 4.1, 0)) plot(xx, yy, type = "l", axes = FALSE, ylim = c(0,5.2), xlim = c(-.3, 5), xlab = "", ylab = "", lwd = 2, main = quote("Parameters in the SSasymp model " ~ {f[phi](x) == phi[1] + (phi[2]-phi[1])*~e^{-e^{phi[3]}*~x}})) mtext(quote(list(phi[1] == "Asym", phi[2] == "R0", phi[3] == "lrc"))) usr <- par("usr") arrows(usr[1], 0, usr[2], 0, length = 0.1, angle = 25) arrows(0, usr[3], 0, usr[4], length = 0.1, angle = 25) text(usr[2] - 0.2, 0.1, "x", adj = c(1, 0)) text( -0.1, usr[4], "y", adj = c(1, 1)) abline(h = 5, lty = 3) arrows(c(0.35, 0.65), 1, c(0 , 1 ), 1, length = 0.08, angle = 25); text(0.5, 1, quote(1)) y0 <- 1 + 4*exp(-3/4) ; t.5 <- log(2) / exp(-3/4) ; AR2 <- 3 # (Asym + R0)/2 segments(c(1, 1), c( 1, y0), c(1, 0), c(y0, 1), lty = 2, lwd = 0.75) text(1.1, 1/2+y0/2, quote((phi[1]-phi[2])*e^phi[3]), adj = c(0,.5)) axis(2, at = c(1,AR2,5), labels= expression(phi[2], frac(phi[1]+phi[2],2), phi[1]), pos=0, las=1) arrows(c(.6,t.5-.6), AR2, c(0, t.5 ), AR2, length = 0.08, angle = 25) text( t.5/2, AR2, quote(t[0.5])) text( t.5 +.4, AR2, quote({f(t[0.5]) == frac(phi[1]+phi[2],2)}~{} \%=>\% {}~~ {t[0.5] == frac(log(2), e^{phi[3]})}), adj = c(0, 0.5)) par(op) } \keyword{models}