Results 71 to 80 of about 3,106 (192)

A joint Bayesian framework for missing data and measurement error using integrated nested Laplace approximations

Biometrical Journal, 2023
AbstractMeasurement error (ME) and missing values in covariates are often unavoidable in disciplines that deal with data, and both problems have separately received considerable attention during the past decades. However, while most researchers are familiar with methods for treating missing data, accounting for ME in covariates of regression models is ...
Emma Skarstein, Sara Martino, Stefanie Muff   +2 more
openaire   +4 more sources

Sparse Minimum Redundancy Maximum Relevance for Feature Selection

Scandinavian Journal of Statistics, EarlyView.
ABSTRACT We propose a feature screening method that integrates both feature–feature and feature–target relationships. Inactive features are identified via a penalized minimum Redundancy Maximum Relevance (mRMR) procedure, which is the continuous version of the classical mRMR penalized by a non‐convex regularizer, and where the parameters estimated as ...
Peter Naylor, Benjamin Poignard, Héctor Climente‐González, Makoto Yamada   +3 more
wiley   +1 more source

Joint quantile disease mapping with application to malaria and G6PD deficiency

Royal Society Open Science
Statistical analysis based on quantile methods is more comprehensive, flexible and less sensitive to outliers when compared to mean methods. Joint disease mapping is useful for inferring correlation between different diseases.
Hanan Alahmadi, Janet van Niekerk, Tullia Padellini, Håvard Rue   +3 more
doaj   +1 more source

Bayesian Spatial Modelling with R-INLA

Journal of Statistical Software, 2015
The principles behind the interface to continuous domain spatial models in the R- INLA software package for R are described. The integrated nested Laplace approximation (INLA) approach proposed by Rue, Martino, and Chopin (2009) is a computationally ...
Finn Lindgren, Håvard Rue
doaj   +1 more source

survHE: Survival Analysis for Health Economic Evaluation and Cost-Effectiveness Modeling

Journal of Statistical Software, 2020
Survival analysis features heavily as an important part of health economic evaluation, an increasingly important component of medical research. In this setting, it is important to estimate the mean time to the survival endpoint using limited information (
Gianluca Baio
doaj   +1 more source

Bayesian Nonparametric Regression and Density Estimation Using Integrated Nested Laplace Approximations [PDF]

Journal of Biometrics & Biostatistics, 2013
Integrated nested Laplace approximations (INLA) are a recently proposed approximate Bayesian approach to fit structured additive regression models with latent Gaussian field. INLA method, as an alternative to Markov chain Monte Carlo techniques, provides accurate approximations to estimate posterior marginals and avoid time-consuming sampling.
openaire   +2 more sources

Exploring the usefulness of the INLA model in predicting levels of crime in the City of Johannesburg, South Africa

Crime Science
Crime prediction serves as a valuable tool for deriving insightful information that can inform policy decisions at both operational and strategic tiers.
Toshka Coleman, Paul Mokilane, Mapitsi Rangata, Jenny Holloway, Nicolene Botha, Renee Koen, Nontembeko Dudeni-Tlhone   +6 more
doaj   +1 more source

Estimating and predicting snakebite risk in the Terai region of Nepal through a high-resolution geospatial and One Health approach

Scientific Reports, 2021
Most efforts to understand snakebite burden in Nepal have been localized to relatively small areas and focused on humans through epidemiological studies. We present the outcomes of a geospatial analysis of the factors influencing snakebite risk in humans
Carlos Ochoa, Marta Pittavino, Sara Babo Martins, Gabriel Alcoba, Isabelle Bolon, Rafael Ruiz de Castañeda, Stéphane Joost, Sanjib Kumar Sharma, François Chappuis, Nicolas Ray   +9 more
doaj   +1 more source

Confidence Intervals for Price Discovery

Oxford Bulletin of Economics and Statistics, Volume 88, Issue 4, Page 742-764, August 2026.
ABSTRACT This paper discusses asymptotic and bootstrap confidence intervals for multivariate permanent‐transitory decompositions of cointegrated vector autoregressive I(1) systems, with a focus on price discovery. Alternative estimators of the permanent components are compared in terms of efficiency also under separable linear restrictions on the ...
Heino Bohn Nielsen, Paolo Paruolo, Anders Rahbek   +2 more
wiley   +1 more source

Fitting logistic multilevel models with crossed random effects via Bayesian Integrated Nested Laplace Approximations: a simulation study [PDF]

, 2017
Fitting cross-classified multilevel models with binary response is challenging. In this setting a promising method is Bayesian inference through Integrated Nested Laplace Approximations (INLA), which performs well in several latent variable models.
Innocenti, Francesco; id_orcid, Innocenti, Francesco, Francesco Innocenti, Grilli, Leonardo, Leonardo Grilli   +4 more
core   +1 more source