Bayesian inference in nonlinear mixed-effects models using normal independent distributions
Nonlinear mixed-effects (NLME) models are popular in many longitudinal studies, including
those on human immunodeficiency virus (HIV) viral dynamics, pharmacokinetic analysis …
those on human immunodeficiency virus (HIV) viral dynamics, pharmacokinetic analysis …
Robust autoregressive modeling and its diagnostic analytics with a COVID-19 related application
Autoregressive models in time series are useful in various areas. In this article, we propose
a skew-t autoregressive model. We estimate its parameters using the expectation …
a skew-t autoregressive model. We estimate its parameters using the expectation …
Bayesian analysis of censored linear regression models with scale mixtures of normal distributions
As is the case of many studies, the data collected are limited and an exact value is recorded
only if it falls within an interval range. Hence, the responses can be either left, interval or …
only if it falls within an interval range. Hence, the responses can be either left, interval or …
[PDF][PDF] Bayesian analysis of censored linear regression models with scale mixtures of skew-normal distributions
As is the case of many studies, the data collected are limited and an exact value is recorded
only if it falls within an interval range. Hence, the responses can be either left, interval or …
only if it falls within an interval range. Hence, the responses can be either left, interval or …
Bayesian estimation and case influence diagnostics for the zero-inflated negative binomial regression model
In recent years, there has been considerable interest in regression models based on zero-
inflated distributions. These models are commonly encountered in many disciplines, such as …
inflated distributions. These models are commonly encountered in many disciplines, such as …
Robust joint non-linear mixed-effects models and diagnostics for censored HIV viral loads with CD4 measurement error
Despite technological advances in efficiency enhancement of quantification assays,
biomedical studies on HIV RNA collect viral load responses that are often subject to …
biomedical studies on HIV RNA collect viral load responses that are often subject to …
Bayesian measurement error models using finite mixtures of scale mixtures of skew-normal distributions
CR Barbosa Cabral, NL de Souza… - Journal of Statistical …, 2022 - Taylor & Francis
We present a proposal to deal with the non-normality issue in the context of regression
models with measurement errors when both the response and the explanatory variable are …
models with measurement errors when both the response and the explanatory variable are …
Multivariate measurement error models based on Student-t distribution under censored responses
Measurement error models constitute a wide class of models that include linear and
nonlinear regression models. They are very useful to model many real-life phenomena …
nonlinear regression models. They are very useful to model many real-life phenomena …
Estimation methods for multivariate Tobit confirmatory factor analysis
Tobit confirmatory factor analysis is particularly useful in analysis of multivariate data with
censored information. Two methods for estimating multivariate Tobit confirmatory factor …
censored information. Two methods for estimating multivariate Tobit confirmatory factor …
Partially linear censored regression models using heavy-tailed distributions: A Bayesian approach
Linear regression models where the response variable is censored are often considered in
statistical analysis. A parametric relationship between the response variable and covariates …
statistical analysis. A parametric relationship between the response variable and covariates …