summary.SPQR: summary method for class 'SPQR'

In SPQR: Semi-Parametric Quantile Regression

summary method for class SPQR

Description

summarizes the output produced by SPQR() and structures them in a more organized way to be examined by the user.

Usage

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

Arguments

object	An object of class SPQR.
...	Other arguments.

Value

An object of class summary.SPQR. A list containing summary information of the fitted model.

method	The estimation method
time	The elapsed time
prior	If method = "MAP" or method = "MCMC", the hyperprior model for the variance hyperparameters
model	If method = "MLE" or method = "MAP", the fitted torch model. If method = "MCMC", the posterior samples of neural network parameters
loss	If method = "MLE" or method = "MAP", the train and validation loss
optim.info	If method = "MLE" or method = "MAP", configuration information of the Adam routine
elpd	If method = "MCMC", the expected log-predictive density
diagnostics	If method = "MCMC", diagnostic information of the MCMC chain

Examples

set.seed(919)
n <- 200
X <- rbinom(n, 1, 0.5)
Y <- rnorm(n, X, 0.8)
control <- list(iter = 200, warmup = 150, thin = 1)
fit <- SPQR(X = X, Y = Y, method = "MCMC", control = control,
            normalize = TRUE, verbose = FALSE)

## summarize output
summary(fit)

SPQR documentation built on May 3, 2022, 1:08 a.m.