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