View source: R/summary.mvgam.R
summary.mvgam | R Documentation |
These functions take a fitted mvgam
object and return various useful summaries
## S3 method for class 'mvgam'
summary(object, include_betas = TRUE, smooth_test = TRUE, digits = 2, ...)
## S3 method for class 'mvgam_prefit'
summary(object, ...)
## S3 method for class 'mvgam'
coef(object, summarise = TRUE, ...)
object |
|
include_betas |
Logical. Print a summary that includes posterior summaries
of all linear predictor beta coefficients (including spline coefficients)?
Defaults to |
smooth_test |
Logical. Compute estimated degrees of freedom and approximate
p-values for smooth terms? Defaults to |
digits |
The number of significant digits for printing out the summary;
defaults to |
... |
Ignored |
summarise |
|
summary.mvgam
and summary.mvgam_prefit
return brief summaries of the model's call, along with posterior intervals for
some of the key parameters in the model. Note that some smooths have extra penalties on the null space,
so summaries for the rho
parameters may include more penalty terms than the number of smooths in
the original model formula. Approximate p-values for smooth terms are also returned,
with methods used for their
calculation following those used for mgcv
equivalents (see summary.gam
for details).
The Estimated Degrees of Freedom (edf) for smooth terms is computed using
either edf.type = 1
for models with no trend component, or edf.type = 0
for models with
trend components. These are described in the documentation for jagam
. Experiments suggest
these p-values tend to be more conservative than those that might be returned from an equivalent
model fit with summary.gam
using method = 'REML'
coef.mvgam
returns either summaries or full posterior estimates for GAM
component
coefficients
For summary.mvgam
and summary.mvgam_prefit
, a list
is printed
on-screen showing the summaries for the model
For coef.mvgam
, either a matrix
of posterior coefficient distributions
(if summarise == FALSE
or data.frame
of coefficient summaries)
Nicholas J Clark
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