1% Generated by roxygen2: do not edit by hand
2% Please edit documentation in R/gam-tidiers.R
3\name{tidy.Gam}
4\alias{tidy.Gam}
5\alias{Gam_tidiers}
6\title{Tidy a(n) Gam object}
7\usage{
8\method{tidy}{Gam}(x, ...)
9}
10\arguments{
11\item{x}{A \code{Gam} object returned from a call to \code{\link[gam:gam]{gam::gam()}}.}
12
13\item{...}{Additional arguments. Not used. Needed to match generic
14signature only. \strong{Cautionary note:} Misspelled arguments will be
15absorbed in \code{...}, where they will be ignored. If the misspelled
16argument has a default value, the default value will be used.
17For example, if you pass \code{conf.lvel = 0.9}, all computation will
18proceed using \code{conf.level = 0.95}. Additionally, if you pass
19\code{newdata = my_tibble} to an \code{\link[=augment]{augment()}} method that does not
20accept a \code{newdata} argument, it will use the default value for
21the \code{data} argument.}
22}
23\description{
24Tidy summarizes information about the components of a model.
25A model component might be a single term in a regression, a single
26hypothesis, a cluster, or a class. Exactly what tidy considers to be a
27model component varies across models but is usually self-evident.
28If a model has several distinct types of components, you will need to
29specify which components to return.
30}
31\details{
32Tidy \code{gam} objects created by calls to \code{\link[mgcv:gam]{mgcv::gam()}} with
33\code{\link[=tidy.gam]{tidy.gam()}}.
34}
35\examples{
36
37if (requireNamespace("gam", quietly = TRUE)) {
38
39library(gam)
40g <- gam(mpg ~ s(hp, 4) + am + qsec, data = mtcars)
41
42tidy(g)
43glance(g)
44
45}
46
47}
48\seealso{
49\code{\link[=tidy]{tidy()}}, \code{\link[gam:gam]{gam::gam()}}, \code{\link[=tidy.anova]{tidy.anova()}}, \code{\link[=tidy.gam]{tidy.gam()}}
50
51Other gam tidiers:
52\code{\link{glance.Gam}()}
53}
54\concept{gam tidiers}
55\value{
56A \code{\link[tibble:tibble]{tibble::tibble()}} with columns:
57  \item{df}{Degrees of freedom used by this term in the model.}
58  \item{meansq}{Mean sum of squares. Equal to total sum of squares divided by degrees of freedom.}
59  \item{p.value}{The two-sided p-value associated with the observed statistic.}
60  \item{statistic}{The value of a T-statistic to use in a hypothesis that the regression term is non-zero.}
61  \item{sumsq}{Sum of squares explained by this term.}
62  \item{term}{The name of the regression term.}
63
64}
65