imputeSS: Missing values' imputation

In GJRM: Generalised Joint Regression Modelling

Missing values' imputation

Description

imputeSS imputes missing values for a gjrm model object.

Usage

imputeSS(x, m = 10)

Arguments

x	A fitted gjrm object.
m	Number of imputed response vectors.

Details

This function generates m sets of imputed values for the outcome of interest under a fitted copulaSampleSel model. The algorithm draws parameters from the posterior distribution of copulaSampleSel which are then used to obtain simulated responses (from the posterior predictive distribution of the missing values) via a rejection algorithm. The bound for acceptance/rejection is obtained via a trust region optimisation.

The imputed values are used to create m complete imputed datasets and perform complete data analysis and inference about the parameters of interest using function gamlss() within this package.

Value

It returns a list containing m imputed response vectors.

Author(s)

Authors: Jose Camarena, Giampiero Marra and Rosalba Radice

Maintainer: Giampiero Marra [e-mail]

References

Robert C. and Casella G. (2004). Monte Carlo Statistical Methods. New York: Springer-Verlag.

Ripley B. D. (1987) Stochastic Simulation. New York: John Wiley & Sons, Inc.

See Also

gjrm

Examples

## see examples for gjrm

GJRM documentation built on July 9, 2023, 7:15 p.m.