EVOLUTION-MANAGER
Edit File: vcov.gam.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: Extract parameter (estimator) covariance matrix from GAM fit</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 vcov.gam {mgcv}"><tr><td>vcov.gam {mgcv}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2>Extract parameter (estimator) covariance matrix from GAM fit</h2> <h3>Description</h3> <p> Extracts the Bayesian posterior covariance matrix of the parameters or frequentist covariance matrix of the parameter estimators from a fitted <code>gam</code> object. </p> <h3>Usage</h3> <pre> ## S3 method for class 'gam' vcov(object, freq = FALSE, dispersion = NULL,unconditional=FALSE, ...) </pre> <h3>Arguments</h3> <table summary="R argblock"> <tr valign="top"><td><code>object</code></td> <td> <p> fitted model object of class <code>gam</code> as produced by <code>gam()</code>.</p> </td></tr> <tr valign="top"><td><code>freq</code></td> <td> <p><code>TRUE</code> to return the frequentist covariance matrix of the parameter estimators, <code>FALSE</code> to return the Bayesian posterior covariance matrix of the parameters.</p> </td></tr> <tr valign="top"><td><code>dispersion</code></td> <td> <p> a value for the dispersion parameter: not normally used.</p> </td></tr> <tr valign="top"><td><code>unconditional</code></td> <td> <p> if <code>TRUE</code> (and <code>freq==FALSE</code>) then the Bayesian smoothing parameter uncertainty corrected covariance matrix is returned, if available. </p> </td></tr> <tr valign="top"><td><code>...</code></td> <td> <p> other arguments, currently ignored.</p> </td></tr> </table> <h3>Details</h3> <p> Basically, just extracts <code>object$Ve</code> or <code>object$Vp</code> from a <code><a href="gamObject.html">gamObject</a></code>. </p> <h3>Value</h3> <p> A matrix corresponding to the estimated frequentist covariance matrix of the model parameter estimators/coefficients, or the estimated posterior covariance matrix of the parameters, depending on the argument <code>freq</code>. </p> <h3>Author(s)</h3> <p> Henric Nilsson. Maintained by Simon N. Wood <a href="mailto:simon.wood@r-project.org">simon.wood@r-project.org</a> </p> <h3>References</h3> <p>Wood, S.N. (2006) On confidence intervals for generalized additive models based on penalized regression splines. Australian and New Zealand Journal of Statistics. 48(4): 445-464. </p> <h3>See Also</h3> <p><code><a href="gam.html">gam</a></code></p> <h3>Examples</h3> <pre> require(mgcv) n <- 100 x <- runif(n) y <- sin(x*2*pi) + rnorm(n)*.2 mod <- gam(y~s(x,bs="cc",k=10),knots=list(x=seq(0,1,length=10))) diag(vcov(mod)) </pre> <hr /><div style="text-align: center;">[Package <em>mgcv</em> version 1.8-28 <a href="00Index.html">Index</a>]</div> </body></html>