Jim E. Griffin

发表

Stephen G. Walker, Jim E. Griffin, 2013, Stat. Comput..

Sequential Monte Carlo methods for mixtures with normalized random measures with independent increments priors

Jim E. Griffin, J. Griffin, 2017, Stat. Comput..

Adaptive Monte Carlo for Bayesian Variable Selection in Regression Models

Jim E. Griffin, Mark F. J. Steel, Demetris Lamnisos, 2013 .

Bayesian inference with stochastic volatility models using continuous superpositions of non-Gaussian Ornstein-Uhlenbeck processes

Jim E. Griffin, Mark F. J. Steel, M. Steel, 2010, Comput. Stat. Data Anal..

Modeling overdispersion with the normalized tempered stable distribution

Jim E. Griffin, Mark F. J. Steel, M. Kolossiatis, 2011, Comput. Stat. Data Anal..

Slice sampling mixture models

Stephen G. Walker, Jim E. Griffin, Maria Kalli, 2011, Stat. Comput..

On a Bayesian Approach to Malware Detection and Classification through n-gram Profiles pdf

Jim E. Griffin, Jos'e A. Perusqu'ia, Cristiano Villa, 2020, ArXiv.

Bayesian stochastic frontier analysis using WinBUGS

Jim E. Griffin, Mark F. J. Steel, M. Steel, 2007 .

A Bayesian Partition Model for Customer Attrition

Jim E. Griffin, Clive Hoggart, 2001 .

Discussion of “Nonparametric Bayesian Inference in Applications”: Bayesian nonparametric methods in econometrics

Jim E. Griffin, Mark F. J. Steel, Maria Kalli, 2018, Stat. Methods Appl..

On Bayesian nonparametric modelling of two correlated distributions

Jim E. Griffin, Mark F. J. Steel, M. Kolossiatis, 2013, Stat. Comput..

Flexible and Nonparametric Methods

Jim E. Griffin, Mark F. J. Steel, Fernando A. Quintana, 2011 .

An adaptive truncation method for inference in Bayesian nonparametric models

Jim E. Griffin, J. Griffin, 2013, Statistics and Computing.

An adaptive MCMC method for Bayesian variable selection in logistic and accelerated failure time regression models

Jim E. Griffin, Kitty Yuen Yi Wan, J. Griffin, 2021, Stat. Comput..

ParticleMDI: particle Monte Carlo methods for the cluster analysis of multiple datasets with applications to cancer subtype identification

Jim E. Griffin, David L. Wild, Nathan Cunningham, 2020, Adv. Data Anal. Classif..

Bayesian Models Applied to Cyber Security Anomaly Detection Problems pdf

Jim E. Griffin, Cristiano Villa, Jos'e A. Perusqu'ia, 2020, ArXiv.

Discovering transcriptional modules by Bayesian data integration

Zoubin Ghahramani, Jim E. Griffin, David L. Wild, 2010, Bioinform..

Cross-validation prior choice in Bayesian probit regression with many covariates

Jim E. Griffin, Mark F. J. Steel, D. Lamnisos, 2012, Stat. Comput..

Estimating The Probability of Informed Trading: A Bayesian Approach

Jaideep S Oberoi, Jim E. Griffin, Samuel Dua Oduro, 2018, Journal of Banking & Finance.

Modelling environmental DNA data; Bayesian variable selection accounting for false positive and false negative errors

Jim E. Griffin, Eleni Matechou, Andrew S. Buxton, 2019, Journal of the Royal Statistical Society: Series C (Applied Statistics).

A Polya Tree Based Model for Unmarked Individuals in an Open Wildlife Population

Jim E. Griffin, Alex Diana, Eleni Matechou, 2018 .

Zoubin Ghahramani, Jim E. Griffin, Paul D. W. Kirk, 2012, Bioinform..

A Bayesian Quantile Time Series Model for Asset Returns

Jim E. Griffin, Gelly Mitrodima, 2020 .

A Bayesian Semiparametric Model for Volatility with a Leverage Effect

Jim E. Griffin, E.-I. Delatola, J. Griffin, 2011, Comput. Stat. Data Anal..

Flexible and Nonparametric Modeling

Jim E. Griffin, Mark F. J. Steel, Fernando A. Quintana, 2011 .

particleMDI: A Julia Package for the Integrative Cluster Analysis of Multiple Datasets

Jim E. Griffin, Anthony Lee, David L. Wild, 2018, Springer Proceedings in Mathematics & Statistics.

Bayesian global-local shrinkage methods for regularisation in the high dimension linear model

Jim E. Griffin, Philip J. Brown, 2021 .

Inference in Infinite Superpositions of Non-Gaussian Ornstein--Uhlenbeck Processes Using Bayesian Nonparametic Methods

Jim E. Griffin, J. Griffin, 2011 .

Identifying cancer subtypes in glioblastoma by combining genomic, transcriptomic and epigenomic data

Zoubin Ghahramani, Jim E. Griffin, David L. Wild, 2013 .

Proceedings of the 21st International Workshop on Statistical Modelling

Jim E. Griffin, Philip J. Brown, J. Griffin, 2006 .

Structuring shrinkage: some correlated priors for regression

Jim E. Griffin, Philip J. Brown, 2012 .

Default priors for density estimation with mixture models

Jim E. Griffin, J. Griffin, 2010 .

Hierarchical Shrinkage Priors for Regression Models

Jim E. Griffin, Philip J. Brown, J. Griffin, 2017 .

Stick-breaking autoregressive processes

Jim E. Griffin, Mark F. J. Steel, M. Steel, 2011 .

Bayesian Nonparametric Vector Autoregressive Models

Jim E. Griffin, Maria Kalli, J. Griffin, 2017 .

Transdimensional Sampling Algorithms for Bayesian Variable Selection in Classification Problems With Many More Variables Than Observations

Jim E. Griffin, Mark F. J. Steel, Demetris Lamnisos, 2009 .

On the Bayesian analysis of species sampling mixture models for density estimation

Jim E. Griffin, J. Griffin, 2006 .