Results 51 to 60 of about 1,207 (171)

On the reduction of Gaussian inverse Wishart mixtures

, 2012
This paper presents an algorithm for reduction of Gaussian inverse Wishart mixtures. Sums of an arbitrary number of mixture components are approximated with single components by analytically minimizing the Kullback-Leibler divergence.
Orguner, Umut, Granström, Karl
core   +1 more source

On the Foundational Arguments of Sufficient Dimension Reduction

WIREs Computational Statistics, Volume 18, Issue 2, June 2026.
Contemporary Sufficient Dimension Reduction, a versatile method for extracting material information from data, can serve as a preprocessor for classical modeling and inference, or as a standalone theory that leads directly to statistical inference. ABSTRACT Sufficient dimension reduction (SDR) refers to supervised methods of dimension reduction that ...
R. Dennis Cook
wiley   +1 more source

Nonparametric estimation of covariance functions by model selection [PDF]

, 2009
We propose a model selection approach for covariance estimation of a stochastic process. Under very general assumptions, observing i.i.d replications of the process at fixed observation points, we construct an estimator of the covariance function by ...
Muniz Alvarez, Lilian, Muñiz-Alvarez, Lilian, Biscay, Rolando, Lilian, Muniz-Alvarez, Jérémie Bigot, Lilian Muñiz-Alvarez, Bigot, Jérémie, Rolando Biscay, Jean-Michel Loubes, Loubes, Jean-Michel   +9 more
core   +1 more source

A Mixed Frequency BVAR for the Australian Economy*

Economic Record, Volume 102, Issue 337, Page 182-207, June 2026.
A mixed frequency vector autoregression (MFVAR) model is proposed for nowcasting, forecasting and backcasting Australian macroeconomic indicators at monthly and quarterly frequencies. A novel augmented Minnesota prior for MFVAR models is also introduced.
Kelly Trinh, Jamie L. Cross
wiley   +1 more source

Bayesian Inference for Joint Estimation Models Using Copulas to Handle Endogenous Regressors

Oxford Bulletin of Economics and Statistics, Volume 88, Issue 3, Page 519-534, June 2026.
ABSTRACT This study proposes a Bayesian approach for finite‐sample inference of the Gaussian copula endogeneity correction. Extant studies use frequentist inference, build on a priori computed estimates of marginal distributions of explanatory variables, and use bootstrapping to obtain standard errors. The proposed Bayesian approach facilitates precise
Rouven E. Haschka
wiley   +1 more source

A Novel Robust Student’s t-Based Cubature Information Filter with Heavy-Tailed Noises

International Journal of Aerospace Engineering, 2020
In this paper, a novel robust Student’s t-based cubature information filter is proposed for a nonlinear multisensor system with heavy-tailed process and measurement noises.
Yongtao Shui, Xiaogang Wang, Wutao Qin, Yu Wang, Baojun Pang, Naigang Cui   +5 more
doaj   +1 more source

Bayesian Poisson‐Lognormal Regression With Compositional Effect Shares for Multivariate Count Data

Environmetrics, Volume 37, Issue 4, May 2026.
ABSTRACT Multivariate count data are central in community ecology and related fields, where interest lies in how environmental gradients and management actions jointly shape the abundances of many taxa. The Poisson‐lognormal (PLN) model is a natural workhorse in this setting, accommodating overdispersion and cross‐taxon dependence via a latent Gaussian
Abdolnasser Sadeghkhani
wiley   +1 more source

A Variational Bayesian Adaptive Kalman Filter for the Random Losses Problem of Sensor Packet

IEEE Access
In this paper, a variational Bayesian adaptive Kalman filter (VBAKF) was used to solve the impact of unknown non-Gaussian measurement noise (NGMN) and sensor measurement loss in Wireless Sensor Networks (WSN) communication. First, the inverse Wishart (IW)
Changzhong Chen, Dahai Shu, Xie Leng, Haijun Long, Han Wu   +4 more
doaj   +1 more source

Multi‐Level Variable Selection Using a BART‐Enhanced Mixed‐Effects Framework

Statistics in Medicine, Volume 45, Issue 10-12, May 2026.
ABSTRACT Selecting important individual‐ and cluster‐level predictors has become increasingly critical in healthcare research, where data often exhibit hierarchical structures due to collection from multiple clusters. Mixed‐effects models, which account for within‐cluster correlation and between‐cluster heterogeneity, are a natural approach for ...
Keming Zhang, Yaoyao Li, Jungang Zou, Sijian Wang, Bernadette A. Fausto, Liangyuan Hu   +5 more
wiley   +1 more source

Superstatistical generalisations of Wishart-Laguerre ensembles of random matrices

, 2008
Using Beck and Cohen's superstatistics, we introduce in a systematic way a family of generalized Wishart–Laguerre ensembles of random matrices with Dyson index β = 1, 2 and 4. The entries of the data matrix are Gaussian random variables whose variances η
Akemann, G, Vivo, P., Vivo, P, Abul-Magd, A. Y., Akemann, Gernot, Abul-Magd, AY   +5 more
core   +1 more source