EVOLUTION-MANAGER
Edit File: tidy.ridgelm.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: Tidy a(n) ridgelm object</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 tidy.ridgelm {broom}"><tr><td>tidy.ridgelm {broom}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2>Tidy a(n) ridgelm object</h2> <h3>Description</h3> <p>Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return. </p> <h3>Usage</h3> <pre> ## S3 method for class 'ridgelm' tidy(x, ...) </pre> <h3>Arguments</h3> <table summary="R argblock"> <tr valign="top"><td><code>x</code></td> <td> <p>A <code>ridgelm</code> object returned from <code><a href="../../MASS/html/lm.ridge.html">MASS::lm.ridge()</a></code>.</p> </td></tr> <tr valign="top"><td><code>...</code></td> <td> <p>Additional arguments. Not used. Needed to match generic signature only. <strong>Cautionary note:</strong> Misspelled arguments will be absorbed in <code>...</code>, where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass <code>conf.lvel = 0.9</code>, all computation will proceed using <code>conf.level = 0.95</code>. Additionally, if you pass <code>newdata = my_tibble</code> to an <code><a href="reexports.html">augment()</a></code> method that does not accept a <code>newdata</code> argument, it will use the default value for the <code>data</code> argument.</p> </td></tr> </table> <h3>Value</h3> <p>A <code><a href="../../tibble/html/tibble.html">tibble::tibble()</a></code> with columns: </p> <table summary="R valueblock"> <tr valign="top"><td><code>GCV</code></td> <td> <p>Generalized cross validation error estimate.</p> </td></tr> <tr valign="top"><td><code>lambda</code></td> <td> <p>Value of penalty parameter lambda.</p> </td></tr> <tr valign="top"><td><code>term</code></td> <td> <p>The name of the regression term.</p> </td></tr> <tr valign="top"><td><code>estimate</code></td> <td> <p>estimate of scaled coefficient using this lambda</p> </td></tr> <tr valign="top"><td><code>scale</code></td> <td> <p>Scaling factor of estimated coefficient</p> </td></tr> </table> <h3>See Also</h3> <p><code><a href="reexports.html">tidy()</a></code>, <code><a href="../../MASS/html/lm.ridge.html">MASS::lm.ridge()</a></code> </p> <p>Other ridgelm tidiers: <code><a href="glance.ridgelm.html">glance.ridgelm</a>()</code> </p> <h3>Examples</h3> <pre> names(longley)[1] <- "y" fit1 <- MASS::lm.ridge(y ~ ., longley) tidy(fit1) fit2 <- MASS::lm.ridge(y ~ ., longley, lambda = seq(0.001, .05, .001)) td2 <- tidy(fit2) g2 <- glance(fit2) # coefficient plot library(ggplot2) ggplot(td2, aes(lambda, estimate, color = term)) + geom_line() # GCV plot ggplot(td2, aes(lambda, GCV)) + geom_line() # add line for the GCV minimizing estimate ggplot(td2, aes(lambda, GCV)) + geom_line() + geom_vline(xintercept = g2$lambdaGCV, col = "red", lty = 2) </pre> <hr /><div style="text-align: center;">[Package <em>broom</em> version 0.7.0 <a href="00Index.html">Index</a>]</div> </body></html>