s4_generics: S4 generics for lgpfit, lgpmodel, and other objects

In lgpr: Longitudinal Gaussian Process Regression

S4 generics for lgpfit, lgpmodel, and other objects

Description

S4 generics for lgpfit, lgpmodel, and other objects

Usage

parameter_info(object, digits)

component_info(object)

covariate_info(object)

component_names(object)

get_model(object)

is_f_sampled(object)

get_stanfit(object)

postproc(object, ...)

contains_postproc(object)

clear_postproc(object)

num_paramsets(object)

num_evalpoints(object)

num_components(object)

Arguments

object	object for which to apply the generic
digits	number of digits to show
...	additional optional arguments to pass

Value

• parameter_info returns a data frame with one row for each parameter and columns for parameter name, parameter bounds, and the assigned prior

• component_info returns a data frame with one row for each model component, and columns encoding information about model components

• covariate_info returns a list with names continuous and categorical, with information about both continuous and categorical covariates

• component_names returns a character vector with component names

• get_model for lgpfit objects returns an lgpmodel

• is_f_sampled returns a logical value

• get_stanfit returns a stanfit (rstan)

• postproc applies postprocessing and returns an updated lgpfit

• clear_postproc removes postprocessing information and returns an updated lgpfit

• num_paramsets, num_evalpoints and num_components return an integer

Functions

• parameter_info(): Get parameter information (priors etc.).

• component_info(): Get component information.

• covariate_info(): Get covariate information.

• component_names(): Get component names.

• get_model(): Get lgpmodel object.

• is_f_sampled(): Determine if signal f is sampled or marginalized.

• get_stanfit(): Extract stanfit object.

• postproc(): Perform postprocessing.

• contains_postproc(): Determine if object contains postprocessing information.

• clear_postproc(): Clear postprocessing information (to reduce size of object).

• num_paramsets(): Get number of parameter sets.

• num_evalpoints(): Get number of points where posterior is evaluated.

• num_components(): Get number of model components.

See Also

To find out which methods have been implemented for which classes, see lgpfit, lgpmodel, Prediction and GaussianPrediction.

lgpr documentation built on Sept. 24, 2023, 9:06 a.m.