summary.mp_estimate: Multiprobit Summary Information

In finnlindgren/multiprobit: Bayesian Multivariate Probit Regression

Multiprobit Summary Information

Description

Organise information about multiprobit parameter estimates and models

Usage

## S3 method for class 'mp_estimate'
summary(object, ...)

## S3 method for class 'mp_model'
summary(object, ...)

Arguments

object	An mp_estimate or mp_modelobject
...	Additional parameters, currently unused.

Value

An mp_estimate_summary or mp_model_summary list object with elements

beta

Summary information about the B coefficients (see mp_model() for model definition). The elements of the matrix B are listed row-wise, so that the values for each covariate are grouped together, for all Y-dimensions.

u

Summary information about the latent u parameters (see mp_model() for model definition). This is the internal scale representation of the probit correlation matrix parameter \Sigma.

Sigma

Summary information for \Sigma. Includes a basic linear error propagation estimate of the elementwise standard deviations, as ⁠[prior_]sd_linear⁠; the calculation for the prior in mp_model indicates that this is an overestimate of the actual standard deviations of the \Sigma elements.

For model summaries, the prior mean and standard deviations are provided. For estimate summaries, the available quantities depend on what was computed and stored in the input object. Currently, the latent MAP estimates and their Hessian-based uncertainties are provided, and the corresponding point estimate of the probit correlation matrix parameter \Sigma.

Examples

## Not run: 
if (interactive()) {
  # EXAMPLE1
}

## End(Not run)

finnlindgren/multiprobit documentation built on June 14, 2025, 1:12 p.m.