EVOLUTION-MANAGER
Edit File: rms.curv.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: Relative Curvature Measures for Non-Linear Regression</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 rms.curv {MASS}"><tr><td>rms.curv {MASS}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2> Relative Curvature Measures for Non-Linear Regression </h2> <h3>Description</h3> <p>Calculates the root mean square parameter effects and intrinsic relative curvatures, <i>c^theta</i> and <i>c^iota</i>, for a fitted nonlinear regression, as defined in Bates & Watts, section 7.3, p. 253ff </p> <h3>Usage</h3> <pre> rms.curv(obj) </pre> <h3>Arguments</h3> <table summary="R argblock"> <tr valign="top"><td><code>obj</code></td> <td> <p>Fitted model object of class <code>"nls"</code>. The model must be fitted using the default algorithm. </p> </td></tr> </table> <h3>Details</h3> <p>The method of section 7.3.1 of Bates & Watts is implemented. The function <code>deriv3</code> should be used generate a model function with first derivative (gradient) matrix and second derivative (Hessian) array attributes. This function should then be used to fit the nonlinear regression model. </p> <p>A print method, <code>print.rms.curv</code>, prints the <code>pc</code> and <code>ic</code> components only, suitably annotated. </p> <p>If either <code>pc</code> or <code>ic</code> exceeds some threshold (0.3 has been suggested) the curvature is unacceptably high for the planar assumption. </p> <h3>Value</h3> <p>A list of class <code>rms.curv</code> with components <code>pc</code> and <code>ic</code> for parameter effects and intrinsic relative curvatures multiplied by sqrt(F), <code>ct</code> and <code>ci</code> for <i>c^θ</i> and <i>c^ι</i> (unmultiplied), and <code>C</code> the C-array as used in section 7.3.1 of Bates & Watts. </p> <h3>References</h3> <p>Bates, D. M, and Watts, D. G. (1988) <em>Nonlinear Regression Analysis and its Applications.</em> Wiley, New York. </p> <h3>See Also</h3> <p><code><a href="../../stats/html/deriv.html">deriv3</a></code> </p> <h3>Examples</h3> <pre> # The treated sample from the Puromycin data mmcurve <- deriv3(~ Vm * conc/(K + conc), c("Vm", "K"), function(Vm, K, conc) NULL) Treated <- Puromycin[Puromycin$state == "treated", ] (Purfit1 <- nls(rate ~ mmcurve(Vm, K, conc), data = Treated, start = list(Vm=200, K=0.1))) rms.curv(Purfit1) ##Parameter effects: c^theta x sqrt(F) = 0.2121 ## Intrinsic: c^iota x sqrt(F) = 0.092 </pre> <hr /><div style="text-align: center;">[Package <em>MASS</em> version 7.3-51.4 <a href="00Index.html">Index</a>]</div> </body></html>