A general Bayesian model for heteroskedastic data with fully conjugate full-conditional distributions
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Statistical Computation and Simulation"
DOI: 10.1080/00949655.2021.1925279
Abstract: Models for heteroskedastic data are relevant in a variety of applications ranging from financial time series to environmental statistics. However, the topic of modelling the variance function conditionally has not seen as much attention as… read more here.
Keywords: model heteroskedastic; heteroskedastic data; model; full conditional ... See more keywords
Fast and Accurate Approximation of the Full Conditional for Gamma Shape Parameters
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Computational and Graphical Statistics"
DOI: 10.1080/10618600.2018.1537929
Abstract: Abstract The gamma distribution arises frequently in Bayesian models, but there is not an easy-to-use conjugate prior for the shape parameter of a gamma. This inconvenience is usually dealt with by using either Metropolis–Hastings moves,… read more here.
Keywords: shape; approximation; full conditional; gamma distribution ... See more keywords
Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model
Sign Up to like & getrecommendations! Published in 2018 at "Statistical Methods in Medical Research"
DOI: 10.1177/0962280216665872
Abstract: Estimating the parameters of a regression model of interest is complicated by missing data on the variables in that model. Multiple imputation is commonly used to handle these missing data. Joint model multiple imputation and… read more here.
Keywords: imputation; conditional specification; multiple imputation; joint model ... See more keywords