35 citations · 70 across the 16 of their papers we have counts for
18 papers
Informative Distance-Based Priors for Correlation Matrices Centred on a Target Reference
Anna Freni-Sterrantino, Janet van Niekerk, Elias Teixeira Krainski +3
Specifying a prior over the space of correlation matrices is a persistent challenge in Bayesian analysis. The space is a curved manifold whose dimension grows quadratically with th…
A flexible wrapped Lindley-type distribution for angular data modelling
Johan Ferreira, Delene van Wyk-de Ridder, Janet van Niekerk
Flexible distributions for modelling angular data have received considerable attention in recent years, with ongoing work extending existing circular models to provide greater flex…
A robust contaminated discrete Weibull regression model for outlier-prone count data
Divan A. Burger, Janet van Niekerk, Emmanuel Lesaffre
Count data often exhibit overdispersion driven by heavy tails or excess zeros, making standard models (e.g., Poisson, negative binomial) insufficient for handling outlying observat…
Penalizing complexity priors for Bayesian inference of circular models
Xiang Ye, Janet Van Niekerk, Håvard Rue
Advancements in computational power and methodologies have enabled research on massive datasets. However, tools for analyzing data with directional or periodic characteristics, suc…
Joint Modeling of Multivariate Longitudinal and Survival Outcomes with the R package INLAjoint
Denis Rustand, Janet van Niekerk, Elias Teixeira Krainski +1
This paper introduces the R package INLAjoint, designed as a toolbox for fitting a diverse range of regression models addressing both longitudinal and survival outcomes. INLAjoint…
A graphical framework for interpretable correlation matrix models
Anna Freni Sterrantino, Denis Rustand, Janet van Niekerk +2
In this work, we present a new approach for constructing models for correlation matrices with a user-defined graphical structure. The graphical structure makes correlation matrices…
Spatio-temporal insights for wind energy harvesting in South Africa
Matthew de Bie, Janet van Niekerk, Andriette Bekker
Understanding complex spatial dependency structures is a crucial consideration when attempting to build a modeling framework for wind speeds. Ideally, wind speed modeling should be…
Bayesian survival analysis with INLA
Danilo Alvares, Janet van Niekerk, Elias Teixeira Krainski +2
This tutorial shows how various Bayesian survival models can be fitted using the integrated nested Laplace approximation in a clear, legible, and comprehensible manner using the IN…
Leave-group-out cross-validation for latent Gaussian models
Zhedong Liu, Janet Van Niekerk, Haavard Rue
Evaluating the predictive performance of a statistical model is commonly done using cross-validation. Among the various methods, leave-one-out cross-validation (LOOCV) is frequentl…
A new avenue for Bayesian inference with INLA
Janet van Niekerk, Elias Krainski, Denis Rustand +1
Integrated Nested Laplace Approximations (INLA) has been a successful approximate Bayesian inference framework since its proposal by Rue et al. (2009). The increased computational…
Parallelized integrated nested Laplace approximations for fast Bayesian inference
Lisa Gaedke-Merzhäuser, Janet van Niekerk, Olaf Schenk +1
There is a growing demand for performing larger-scale Bayesian inference tasks, arising from greater data availability and higher-dimensional model parameter spaces. In this work w…
Fast and flexible inference for joint models of multivariate longitudinal and survival data using Integrated Nested Laplace Approximations
Denis Rustand, Janet van Niekerk, Elias Teixeira Krainski +2
Modeling longitudinal and survival data jointly offers many advantages such as addressing measurement error and missing data in the longitudinal processes, understanding and quanti…
Joint Posterior Inference for Latent Gaussian Models with R-INLA
Cristian Chiuchiolo, Janet van Niekerk, Haavard Rue
Efficient Bayesian inference remains a computational challenge in hierarchical models. Simulation-based approaches such as Markov Chain Monte Carlo methods are still popular but ha…
Low-rank variational Bayes correction to the Laplace method
Janet van Niekerk, Haavard Rue
Approximate inference methods like the Laplace method, Laplace approximations and variational methods, amongst others, are popular methods when exact inference is not feasible due…
Smart Gradient -- An Adaptive Technique for Improving Gradient Estimation
Esmail Abdul Fattah, Janet Van Niekerk, Haavard Rue
Computing the gradient of a function provides fundamental information about its behavior. This information is essential for several applications and algorithms across various field…
Bayesian Estimation of Two-Part Joint Models for a Longitudinal Semicontinuous Biomarker and a Terminal Event with R-INLA: Interests for Cancer Clinical Trial Evaluation
Denis Rustand, Janet van Niekerk, Håvard Rue +3
Two-part joint models for a longitudinal semicontinuous biomarker and a terminal event have been recently introduced based on frequentist estimation. The biomarker distribution is…
Skewed probit regression -- Identifiability, contraction and reformulation
Janet van Niekerk, Haavard Rue
Skewed probit regression is but one example of a statistical model that generalizes a simpler model, like probit regression. All skew-symmetric distributions and link functions ari…
Bayesian Analysis of AR(1) Model
Hossein Masoumi Karakani, Janet van Niekerk, Paul van Staden
The first-order autoregressive process, AR (1), has been widely used and implemented in time series analysis. Different estimation methods have been employed in order to estimate t…