Optimizing production processes is crucial for reducing costs, ensuring product quality, and minimizing downtime. Optimization approaches based on manual parameterization are increasingly reaching ...

Journal of Computational and Graphical Statistics, Vol. 22, No. 3, Special Issue: Advances in Markov Chain Monte Carlo (September 2013), pp. 729-748 (20 pages) This article describes methods for ...

The purpose of the Journal of Computational and Graphical Statistics is to improve and extend the use of computational and graphical methods in statistics and data analysis. Established in 1992, this ...

Profile page for: Nanwei WangMy research interests mainly focus on graphical models, composite likelihood, Bayesian model selection, linear mixed models in genome-wide association study (GWAS). Under ...

We propose a new probabilistic graphical model that jointly models the difficulties of questions, the abilities of participants and the correct answers to questions in aptitude testing and ...

M.Sc. Kari Rantanen defends his doctoral thesis Optimization Algorithms for Learning Graphical Model Structures on Wednesday the 8th of December 2021 at 15 o'clock through remote access. His opponent ...

Hill, J.L. (2011) Bayesian Nonparametric Modeling for Causal Inference. Journal of Computational and Graphical Statistics, 20, 217-240. Login. ... This paper advances a non-parametric autoregressive ...

This article considers the problem to estimate a graphical model corresponding to an autoregressive moving-average (ARMA) Gaussian stochastic process. We propose a new maximum entropy covariance and ...