EVOLUTION-MANAGER
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<!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: Continuous AR(1) Correlation Structure</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 corCAR1 {nlme}"><tr><td>corCAR1 {nlme}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2>Continuous AR(1) Correlation Structure</h2> <h3>Description</h3> <p>This function is a constructor for the <code>corCAR1</code> class, representing an autocorrelation structure of order 1, with a continuous time covariate. Objects created using this constructor must be later initialized using the appropriate <code>Initialize</code> method. </p> <h3>Usage</h3> <pre> corCAR1(value, form, fixed) </pre> <h3>Arguments</h3> <table summary="R argblock"> <tr valign="top"><td><code>value</code></td> <td> <p>the correlation between two observations one unit of time apart. Must be between 0 and 1. Defaults to 0.2.</p> </td></tr> <tr valign="top"><td><code>form</code></td> <td> <p>a one sided formula of the form <code>~ t</code>, or <code>~ t | g</code>, specifying a time covariate <code>t</code> and, optionally, a grouping factor <code>g</code>. Covariates for this correlation structure need not be integer valued. When a grouping factor is present in <code>form</code>, the correlation structure is assumed to apply only to observations within the same grouping level; observations with different grouping levels are assumed to be uncorrelated. Defaults to <code>~ 1</code>, which corresponds to using the order of the observations in the data as a covariate, and no groups.</p> </td></tr> <tr valign="top"><td><code>fixed</code></td> <td> <p>an optional logical value indicating whether the coefficients should be allowed to vary in the optimization, or kept fixed at their initial value. Defaults to <code>FALSE</code>, in which case the coefficients are allowed to vary.</p> </td></tr> </table> <h3>Value</h3> <p>an object of class <code>corCAR1</code>, representing an autocorrelation structure of order 1, with a continuous time covariate. </p> <h3>Author(s)</h3> <p>José Pinheiro and Douglas Bates <a href="mailto:bates@stat.wisc.edu">bates@stat.wisc.edu</a></p> <h3>References</h3> <p>Box, G.E.P., Jenkins, G.M., and Reinsel G.C. (1994) "Time Series Analysis: Forecasting and Control", 3rd Edition, Holden-Day. </p> <p>Jones, R.H. (1993) "Longitudinal Data with Serial Correlation: A State-space Approach", Chapman and Hall. </p> <p>Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S and S-PLUS", Springer, esp. pp. 236, 243. </p> <h3>See Also</h3> <p><code><a href="corClasses.html">corClasses</a></code>, <code><a href="Initialize.corStruct.html">Initialize.corStruct</a></code>, <code><a href="summary.corStruct.html">summary.corStruct</a></code> </p> <h3>Examples</h3> <pre> ## covariate is Time and grouping factor is Mare cs1 <- corCAR1(0.2, form = ~ Time | Mare) # Pinheiro and Bates, pp. 240, 243 fm1Ovar.lme <- lme(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), data = Ovary, random = pdDiag(~sin(2*pi*Time))) fm4Ovar.lme <- update(fm1Ovar.lme, correlation = corCAR1(form = ~Time)) </pre> <hr /><div style="text-align: center;">[Package <em>nlme</em> version 3.1-139 <a href="00Index.html">Index</a>]</div> </body></html>