Results 41 to 50 of about 1,207 (171)

BFDA: A MATLAB Toolbox for Bayesian Functional Data Analysis

Journal of Statistical Software, 2019
We provide a MATLAB toolbox, BFDA, that implements a Bayesian hierarchical model to smooth multiple functional data samples with the assumptions of the same underlying Gaussian process distribution, a Gaussian process prior for the mean function, and an ...
Jingjing Yang, Peng Ren
doaj   +1 more source

Exploring Asymptotic Normality in Multinomial Models

Mathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT Among the methods for analyzing categorical outcomes, the multinomial model offers a robust framework for examining the dependence between a multi‐category response variable and a set of explanatory variables. Its flexibility, versatility, and broad applicability across diverse fields make it a valuable tool, as it does not impose strict ...
Célia Nunes, Isaac Akoto, Carla Santos, João Tiago Mexia   +3 more
wiley   +1 more source

Understanding considerations and priorities in health behaviours: A multi‐dimensional risk–benefit perspective

British Journal of Psychology, EarlyView.
Abstract Health behaviours and decisions are complex and involve different dimensions of individuals' lives. The current study aimed to investigate considerations and their priorities in health decision and behaviour adoption via a risk–benefit framework unifying elements of mainstream models of health behaviour. We aimed to explore the core dimensions
Yiyun Shou, Joey Elizabeth Yeo, Alexander Shao‐Rong Pang   +2 more
wiley   +1 more source

Role of CSN2, CSN3, and BLG genes and the polygenic background in the cattle milk protein profile

Journal of Dairy Science, 2022
: To devise better selection strategies in dairy cattle breeding programs, a deeper knowledge of the role of the major genes encoding for milk protein fractions is required. The aim of the present study was to assess the effect of the CSN2, CSN3, and BLG
Nicolò Amalfitano, Lucio Flavio Macedo Mota, GuilhermeJ.M. Rosa, Alessio Cecchinato, Giovanni Bittante   +4 more
doaj   +1 more source

To vary or not to vary: A flexible empirical Bayes factor for testing variance components

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Random effects are the gold standard for capturing structural heterogeneity, such as individual differences or temporal dependence. Yet testing their presence is difficult because variance components are constrained to be non‐negative, creating a boundary problem. This paper introduces a flexible empirical Bayes factor (EBF) for testing random
Fabio Vieira, Hongwei Zhao, Joris Mulder
wiley   +1 more source

Likelihood Estimation for Stochastic Differential Equations with Mixed Effects

Scandinavian Journal of Statistics, EarlyView.
ABSTRACT Stochastic differential equations provide a powerful tool for modelling dynamic phenomena affected by random noise. When time series are observed for several experimental units, it is often the case that some of the parameters vary between the individual experimental units.
Fernando Baltazar‐Larios, Mogens Bladt, Michael Sørensen   +2 more
wiley   +1 more source

Improved GGIW-PHD filter for maneuvering non-ellipsoidal extended targets or group targets tracking based on sub-random matrices. [PDF]

PLoS ONE, 2018
For non-ellipsoidal extended targets and group targets tracking (NETT and NGTT), using an ellipsoid to approximate the target extension may not be accurate enough because of the lack of shape and orientation information.
Zhibing Liang, Fuxian Liu, Jiale Gao
doaj   +1 more source

Bayesian Distributed Target Detectors in Compound-Gaussian Clutter Against Subspace Interference with Limited Training Data

Remote Sensing
In this article, the problem of Bayesian detecting rank-one distributed targets under subspace interference and compound Gaussian clutter with inverse Gaussian texture is investigated.
Kun Xing, Zhiwen Cao, Weijian Liu, Ning Cui, Zhiyu Wang, Zhongjun Yu, Faxin Yu   +6 more
doaj   +1 more source

Multi-Fading Factor and Updated Monitoring Strategy Adaptive Kalman Filter-Based Variational Bayesian

Sensors, 2020
Aiming at the problem that the performance of adaptive Kalman filter estimation will be affected when the statistical characteristics of the process and measurement of the noise matrices are inaccurate and time-varying in the linear Gaussian state-space ...
Chenghao Shan, Weidong Zhou, Yefeng Yang, Zihao Jiang   +3 more
doaj   +1 more source

Bayesian Frameworks for Explicit Biological Age Estimation

Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 19, Issue 3, June 2026.
ABSTRACT Biological age (BA) is a quantity of interest in insurance, and this paper explores the statistical foundations for estimating an individual's BA, proposing a semi‐parametric Bayesian model for its estimation using multiple quantitative and qualitative phenotypes. BA is modeled explicitly as a latent biological state that influences observable
Stefano Cabras
wiley   +1 more source