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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: Tidy a(n) mle2 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.mle2 {broom}"><tr><td>tidy.mle2 {broom}</td><td style="text-align: right;">R Documentation</td></tr></table> <h2>Tidy a(n) mle2 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 'mle2' tidy(x, conf.int = FALSE, conf.level = 0.95, ...) </pre> <h3>Arguments</h3> <table summary="R argblock"> <tr valign="top"><td><code>x</code></td> <td> <p>An <code>mle2</code> object created by a call to <code><a href="../../bbmle/html/mle2.html">bbmle::mle2()</a></code>.</p> </td></tr> <tr valign="top"><td><code>conf.int</code></td> <td> <p>Logical indicating whether or not to include a confidence interval in the tidied output. Defaults to <code>FALSE</code>.</p> </td></tr> <tr valign="top"><td><code>conf.level</code></td> <td> <p>The confidence level to use for the confidence interval if <code>conf.int = TRUE</code>. Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval.</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>conf.high</code></td> <td> <p>Upper bound on the confidence interval for the estimate.</p> </td></tr> <tr valign="top"><td><code>conf.low</code></td> <td> <p>Lower bound on the confidence interval for the estimate.</p> </td></tr> <tr valign="top"><td><code>estimate</code></td> <td> <p>The estimated value of the regression term.</p> </td></tr> <tr valign="top"><td><code>p.value</code></td> <td> <p>The two-sided p-value associated with the observed statistic.</p> </td></tr> <tr valign="top"><td><code>statistic</code></td> <td> <p>The value of a T-statistic to use in a hypothesis that the regression term is non-zero.</p> </td></tr> <tr valign="top"><td><code>std.error</code></td> <td> <p>The standard error of the regression term.</p> </td></tr> <tr valign="top"><td><code>term</code></td> <td> <p>The name of the regression term.</p> </td></tr> </table> <h3>See Also</h3> <p><code><a href="reexports.html">tidy()</a></code>, <code><a href="../../bbmle/html/mle2.html">bbmle::mle2()</a></code>, <code><a href="tidy_optim.html">tidy_optim()</a></code> </p> <h3>Examples</h3> <pre> library(bbmle) x <- 0:10 y <- c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8) d <- data.frame(x, y) fit <- mle2(y ~ dpois(lambda = ymean), start = list(ymean = mean(y)), data = d ) tidy(fit) </pre> <hr /><div style="text-align: center;">[Package <em>broom</em> version 0.7.0 <a href="00Index.html">Index</a>]</div> </body></html>