seqBART

Dataset of covariate matrix with missing values (NAs).

a vector indicating the type of covariates (0=continuous, 1=binary).

datatype

0=no reponse, 1=continuous response (linear regression used for imputation) and 2=binary response (logistic regression used for imputation)

type

numskip

burn

sigdf

sigquant

kfac

A flexible Bayesian nonparametric model that is used as imputation tool for missing covariates.

Implements the sequential BART (Bayesian Additive
Regression Trees) approach to impute the missing covariates. The
algorithm applies a Bayesian nonparametric approach on factored
sets of sequential conditionals of the joint distribution of the
covariates and the missingness and applying the Bayesian additive
regression trees to model each of these univariate
conditionals. Each conditional distribution is then sampled using
MCMC algorithm. The published journal can be found at
<https://doi.org/10.1093/biostatistics/kxw009> Package provides a
function, seqBART(), which computes and returns the imputed
values.

seqBART: Sequential Bayesian Additive Regression Trees Model

Description

Usage

Arguments

Value