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    the object. Default is \code{FALSE}.}
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    the object. Default is \code{FALSE}.}
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  \item{lower, upper}{vectors of lower and upper bounds, replicated to
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  \item{lower, upper}{vectors of lower and upper bounds, replicated to
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    be as long as \code{start}.  If unspecified, all parameters are
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    be as long as \code{start}.  If unspecified, all parameters are
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    assumed to be unconstrained.  Bounds can only be used with the
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    assumed to be unconstrained.  Bounds can only be used with the
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    \code{"port"} algorithm.  They are ignored, with a warning, if given
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    \code{"port"} algorithm.  They are ignored, with a warning, if given
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    for other algorithms. If given as named vectors, they can be reordered to
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    for other algorithms.}
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    match the coefficient order.}
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  \item{\dots}{Additional optional arguments.  None are used at present.}
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  \item{\dots}{Additional optional arguments.  None are used at present.}
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}
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}
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\details{
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\details{
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  An \code{nls} object is a type of fitted model object.  It has methods
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  An \code{nls} object is a type of fitted model object.  It has methods
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  for the generic functions \code{\link{anova}}, \code{\link{coef}},
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  for the generic functions \code{\link{anova}}, \code{\link{coef}},
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## given in a list (with names):
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## given in a list (with names):
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b <- coef(musc.1)
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b <- coef(musc.1)
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musc.2 <- nls(Length ~ a[Strip] + b[Strip]*exp(-Conc/th), MASS::muscle,
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musc.2 <- nls(Length ~ a[Strip] + b[Strip]*exp(-Conc/th), MASS::muscle,
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              start = list(a = rep(b[2], 21), b = rep(b[3], 21), th = b[1]))
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              start = list(a = rep(b[2], 21), b = rep(b[3], 21), th = b[1]))
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summary(musc.2)
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summary(musc.2)
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## Example with constraint, using "port" algorithm. Also showing possibility
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## for reordering if using named vector for lower=
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dd <- structure(list(time = c(1L, 2L, 3L, 6L, 12L, 24L, 48L), y = c(1.95,
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6.43, 10.39, 27.01, 113.72, 251.14, 314.22)), row.names = c(NA,
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-7L), class = "data.frame")
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st0 <- list(Max = 200, k = 0.1, Lag = 0.5)
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lwr <- c(k = 0.1, Max =-Inf, Lag = -Inf)
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form <- y ~ (time > Lag) * Max * (1-exp(-k * (time - Lag)))
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m1 <- nls(form,
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    data = dd,
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    algorithm="port",
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    lower = lwr,
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    start = st0)
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stopifnot(coef(m1)[["k"]] >= lwr[["k"]])
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})
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})
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}
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}
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\dontshow{options(od)}
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\dontshow{options(od)}
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}
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}
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\keyword{nonlinear}
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\keyword{nonlinear}