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  Originally from Marske (1967), \emph{Biochemical
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  Originally from Marske (1967), \emph{Biochemical
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    Oxygen Demand Data Interpretation Using Sum of Squares Surface}
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    Oxygen Demand Data Interpretation Using Sum of Squares Surface}
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  M.Sc. Thesis, University of Wisconsin -- Madison.
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  M.Sc. Thesis, University of Wisconsin -- Madison.
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}
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}
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\examples{
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\examples{
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\testonly{options(show.nls.convergence=FALSE)
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\dontshow{options(show.nls.convergence=FALSE)
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old <- options(digits = 5)}
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old <- options(digits = 5)}
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require(stats)
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require(stats)
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# simplest form of fitting a first-order model to these data
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# simplest form of fitting a first-order model to these data
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fm1 <- nls(demand ~ A*(1-exp(-exp(lrc)*Time)), data = BOD,
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fm1 <- nls(demand ~ A*(1-exp(-exp(lrc)*Time)), data = BOD,
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   start = c(A = 20, lrc = log(.35)))
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   start = c(A = 20, lrc = log(.35)))
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fm2 <- nls(demand ~ (1-exp(-exp(lrc)*Time)), data = BOD,
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fm2 <- nls(demand ~ (1-exp(-exp(lrc)*Time)), data = BOD,
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   start = c(lrc = log(.35)), algorithm = "plinear", trace = TRUE)
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   start = c(lrc = log(.35)), algorithm = "plinear", trace = TRUE)
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# using a self-starting model
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# using a self-starting model
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fm3 <- nls(demand ~ SSasympOrig(Time, A, lrc), data = BOD)
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fm3 <- nls(demand ~ SSasympOrig(Time, A, lrc), data = BOD)
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summary(fm3)
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summary(fm3)
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\testonly{options(old)}
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\dontshow{options(old)}
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}
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}
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\keyword{datasets}
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\keyword{datasets}