getModelSlots: Return one or slots from the 'Stan' model in 'bayesGAM'

In bayesGAM: Fit Multivariate Response Generalized Additive Models using Hamiltonian Monte Carlo

Return one or slots from the Stan model in bayesGAM

Description

Contains the objects and parameters passed to Stan in object of type glmModel, contained in object type bayesGAMfit

Usage

getModelSlots(object, ...)

## S4 method for signature 'bayesGAMfit'
getModelSlots(object, name = "X")

Arguments

object	Object of type bayesGAMfit
...	Additional arguments for getModelSlots
name	Character name of slot in glmModel X Fixed effects design matrix Z Random effects design matrix Zlst list of individual random effects design matrices that, combined, form Z Zarray array of individual random effects design matrices. Used for multiple response models max_col maximum number of columns of an individual Z matrix. Padding for STAN y numeric response matrix p number of beta parameters r number of eps parameters q number of lambda parameters n number of records in the dataset has_intercept logical of whether the model includes an intercept term zvars number of random effects variables names_beta parameter names for beta names_u parameter names for the random effects names_y response names prior prior object with priors used in the model knots list of knots used in non-parametric functions basis character indicating basis function. tps for thin-plate splines and trunc.poly for truncated polynomial npargs arguments passed to non-parametric functions in the model npterms variables used in non-parametric functions sub_form formula with the np terms removed random_intercept logical indicator of whether a random effects intercept is used multresponse logical indicator of whether the model is multiple response

Value

Contents of slot in glmModel

Examples

require(stats); require(graphics)
f <- bayesGAM(weight ~ np(height), data = women, family = gaussian, 
              iter = 500, chains = 1)
getModelSlots(f, "X")

bayesGAM documentation built on March 18, 2022, 6:29 p.m.