EVOLUTION-MANAGER
Edit File: gamlss.etamu.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: Transform derivatives wrt mu to derivatives wrt linear...</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 gamlss.etamu {mgcv}"><tr><td>gamlss.etamu {mgcv}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2>Transform derivatives wrt mu to derivatives wrt linear predictor</h2> <h3>Description</h3> <p>Mainly intended for internal use in specifying location scale models. Let <code>g(mu) = lp</code>, where <code>lp</code> is the linear predictor, and <code>g</code> is the link function. Assume that we have calculated the derivatives of the log-likelihood wrt <code>mu</code>. This function uses the chain rule to calculate the derivatives of the log-likelihood wrt <code>lp</code>. See <code><a href="trind.generator.html">trind.generator</a></code> for array packing conventions. </p> <h3>Usage</h3> <pre> gamlss.etamu(l1, l2, l3 = NULL, l4 = NULL, ig1, g2, g3 = NULL, g4 = NULL, i2, i3 = NULL, i4 = NULL, deriv = 0) </pre> <h3>Arguments</h3> <table summary="R argblock"> <tr valign="top"><td><code>l1</code></td> <td> <p>array of 1st order derivatives of log-likelihood wrt mu.</p> </td></tr> <tr valign="top"><td><code>l2</code></td> <td> <p>array of 2nd order derivatives of log-likelihood wrt mu.</p> </td></tr> <tr valign="top"><td><code>l3</code></td> <td> <p>array of 3rd order derivatives of log-likelihood wrt mu.</p> </td></tr> <tr valign="top"><td><code>l4</code></td> <td> <p>array of 4th order derivatives of log-likelihood wrt mu.</p> </td></tr> <tr valign="top"><td><code>ig1</code></td> <td> <p>reciprocal of the first derivative of the link function wrt the linear predictor.</p> </td></tr> <tr valign="top"><td><code>g2</code></td> <td> <p>array containing the 2nd order derivative of the link function wrt the linear predictor.</p> </td></tr> <tr valign="top"><td><code>g3</code></td> <td> <p>array containing the 3rd order derivative of the link function wrt the linear predictor.</p> </td></tr> <tr valign="top"><td><code>g4</code></td> <td> <p>array containing the 4th order derivative of the link function wrt the linear predictor.</p> </td></tr> <tr valign="top"><td><code>i2</code></td> <td> <p>two-dimensional index array, such that <code>l2[,i2[i,j]]</code> contains the partial w.r.t. params indexed by i,j with no restriction on the index values (except that they are in 1,...,ncol(l1)).</p> </td></tr> <tr valign="top"><td><code>i3</code></td> <td> <p>third-dimensional index array, such that <code>l3[,i3[i,j,k]]</code> contains the partial w.r.t. params indexed by i,j,k.</p> </td></tr> <tr valign="top"><td><code>i4</code></td> <td> <p>third-dimensional index array, such that <code>l4[,i4[i,j,k,l]]</code> contains the partial w.r.t. params indexed by i,j,k,l.</p> </td></tr> <tr valign="top"><td><code>deriv</code></td> <td> <p>if <code>deriv==0</code> only first and second order derivatives will be calculated. If <code>deriv==1</code> the function goes up to 3rd order, and if <code>deriv==2</code> it provides also 4th order derivatives.</p> </td></tr> </table> <h3>Value</h3> <p>A list where the arrays <code>l1</code>, <code>l2</code>, <code>l3</code>, <code>l4</code> contain the derivatives (up to order four) of the log-likelihood wrt the linear predictor. </p> <h3>Author(s)</h3> <p>Simon N. Wood <simon.wood@r-project.org>. </p> <h3>See Also</h3> <p><code><a href="trind.generator.html">trind.generator</a></code></p> <hr /><div style="text-align: center;">[Package <em>mgcv</em> version 1.8-28 <a href="00Index.html">Index</a>]</div> </body></html>