| % File src/library/datasets/man/BOD.Rd |
| % Part of the R package, https://www.R-project.org |
| % Copyright 1995-2014 R Core Team |
| % Distributed under GPL 2 or later |
| |
| \name{BOD} |
| \docType{data} |
| \alias{BOD} |
| \title{ Biochemical Oxygen Demand } |
| \description{ |
| The \code{BOD} data frame has 6 rows and 2 columns giving the |
| biochemical oxygen demand versus time in an evaluation of water |
| quality. |
| } |
| \usage{BOD} |
| \format{ |
| This data frame contains the following columns: |
| \describe{ |
| \item{\code{Time}}{ |
| A numeric vector giving the time of the measurement (days). |
| } |
| \item{\code{demand}}{ |
| A numeric vector giving the biochemical oxygen demand (mg/l). |
| } |
| } |
| } |
| \source{ |
| Bates, D.M. and Watts, D.G. (1988), |
| \emph{Nonlinear Regression Analysis and Its Applications}, |
| Wiley, Appendix A1.4. |
| |
| Originally from Marske (1967), \emph{Biochemical |
| Oxygen Demand Data Interpretation Using Sum of Squares Surface} |
| M.Sc. Thesis, University of Wisconsin -- Madison. |
| } |
| \examples{ |
| \dontshow{options(show.nls.convergence=FALSE) |
| old <- options(digits = 5)} |
| require(stats) |
| # simplest form of fitting a first-order model to these data |
| fm1 <- nls(demand ~ A*(1-exp(-exp(lrc)*Time)), data = BOD, |
| start = c(A = 20, lrc = log(.35))) |
| coef(fm1) |
| fm1 |
| # using the plinear algorithm |
| fm2 <- nls(demand ~ (1-exp(-exp(lrc)*Time)), data = BOD, |
| start = c(lrc = log(.35)), algorithm = "plinear", trace = TRUE) |
| # using a self-starting model |
| fm3 <- nls(demand ~ SSasympOrig(Time, A, lrc), data = BOD) |
| summary(fm3) |
| \dontshow{options(old)} |
| } |
| \keyword{datasets} |