EVOLUTION-MANAGER
Edit File: BOD.html
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><title>R: Biochemical Oxygen Demand</title> <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /> <link rel="stylesheet" type="text/css" href="R.css" /> </head><body> <table width="100%" summary="page for BOD {datasets}"><tr><td>BOD {datasets}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2> Biochemical Oxygen Demand </h2> <h3>Description</h3> <p>The <code>BOD</code> data frame has 6 rows and 2 columns giving the biochemical oxygen demand versus time in an evaluation of water quality. </p> <h3>Usage</h3> <pre>BOD</pre> <h3>Format</h3> <p>This data frame contains the following columns: </p> <dl> <dt><code>Time</code></dt><dd> <p>A numeric vector giving the time of the measurement (days). </p> </dd> <dt><code>demand</code></dt><dd> <p>A numeric vector giving the biochemical oxygen demand (mg/l). </p> </dd> </dl> <h3>Source</h3> <p>Bates, D.M. and Watts, D.G. (1988), <em>Nonlinear Regression Analysis and Its Applications</em>, Wiley, Appendix A1.4. </p> <p>Originally from Marske (1967), <em>Biochemical Oxygen Demand Data Interpretation Using Sum of Squares Surface</em> M.Sc. Thesis, University of Wisconsin – Madison. </p> <h3>Examples</h3> <pre> 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) </pre> <hr /><div style="text-align: center;">[Package <em>datasets</em> version 3.6.0 <a href="00Index.html">Index</a>]</div> </body></html>