Guoqi Qian

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John L HopperUniversity of MelbourneVerified email at unimelb.edu.au
Enes MakalicProfessor, Faculty of Information Technology, Monash UniversityVerified email at monash.edu
Daniel SchmidtAssociate Professor (Data Science), Faculty of Information Technology, Monash UniversityVerified email at monash.edu
Ning LiUniversity of MelbourneVerified email at unimelb.edu.au
Chris FieldProfessor of Statistics, Dalhousie University, Halifax, CanadaVerified email at mathstat.dal.ca
Daniel ParkThe University of MelbourneVerified email at unimelb.edu.au
Matthias ReumannIBMVerified email at connected-health-insights.com
Zeyu ZhouPhD Student, University of MelbourneVerified email at student.unimelb.edu.au
Kay SheltonSenior Meteorologist, JBA ConsultingVerified email at jbaconsulting.com
Johnny C L ChanEmeritus Professor, City University of Hong KongVerified email at cityu.edu.hk
Frederic HollandeThe University of MelbourneVerified email at unimelb.edu.au
Graham G GilesCancer Council VictoriaVerified email at cancervic.org.au
Adam KowalczykPrincipal Scientist, National ICT AustraliaVerified email at unimelb.edu.au
Robert J. MacInnisCancer Council Victoria & University of MelbourneVerified email at unimelb.edu.au
Melissa C SoutheyChair Precision Medicine, Monash UniversityVerified email at monash.edu
John WagnerIBM Research - AustraliaVerified email at au1.ibm.com
Justin ZobelComputing and Information Systems, University of MelbourneVerified email at unimelb.edu.au
Michael InouyeProfessor of Systems Genomics & Population Health, University of Cambridge; Baker InstituteVerified email at medschl.cam.ac.uk
Liesel M FitzGeraldSenior Research Fellow, Menzies Institute for Medical ResearchVerified email at utas.edu.au
Daniel F. SchmidtLuxembourg Institute of Science & Technology / University of Massachusetts LowellVerified email at list.lu

Guoqi Qian

University of Melbourne

Verified email at ms.unimelb.edu.au - Homepage


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Selection of working correlation structure and best model in GEE analyses of longitudinal data J Cui, G Qian Communications in statistics—Simulation and computation® 36 (5), 987-996, 2007	175	2007
Principal components selection by the criterion of the minimum mean difference of complexity GQ Qian, G Gabor, RP Gupta Journal of multivariate analysis 49 (1), 55-75, 1994	49	1994
Some notes on Rissanen's stochastic complexity G Qian, HR Kunsch IEEE Transactions on Information Theory 44 (2), 782-786, 1998	36	1998
On model selection via stochastic complexity in robust linear regression G Qian, HR Künsch Journal of Statistical Planning and Inference 75 (1), 91-116, 1998	30	1998
Using MCMC for logistic regression model selection involving large number of candidate models G Qian, C Field Monte Carlo and Quasi-Monte Carlo Methods 2000: Proceedings of a Conference …, 2002	29	2002
Stock Price Prediction Using a Frequency Decomposition Based GRU Transformer Neural Network C Li, G Qian Applied Sciences 13 (1), 222, 2022	27	2022
Law of iterated logarithm and consistent model selection criterion in logistic regression G Qian, C Field Statistics & probability letters 56 (1), 101-112, 2002	27	2002
Generalised linear model selection by the predictive least quasi-deviance criterion G Qian, G Gabor, RP Gupta Biometrika 83 (1), 41-54, 1996	25	1996
Spline-based modelling of near-surface wind speeds in tropical cyclones JS Wijnands, G Qian, Y Kuleshov Applied Mathematical Modelling 40 (19-20), 8685-8707, 2016	24	2016
Spatial sampling design based on stochastic complexity MC Bueso, JM Angulo, G Qian, FJ Alonso Journal of multivariate analysis 71 (1), 94-110, 1999	24	1999
Seasonal forecasting of tropical cyclone activity in the Australian and the South Paci c Ocean regions J Wijnands, G Qian, KL Shelton, RJB Fawcett, JCL Chan, Y Kuleshov Mathematics of Climate and Weather Forecasting 1, 21-42, 2015	22	2015
On time series model selection involving many candidate ARMA models G Qian, X Zhao Computational Statistics & Data Analysis 51 (12), 6180-6196, 2007	22	2007
On model selection in robust linear regression G Qian, H Künsch Research report/Seminar für Statistik, Eidgenössische Technische Hochschule …, 1996	21	1996
Variable selection for tropical cyclogenesis predictive modeling JS Wijnands, G Qian, Y Kuleshov Monthly Weather Review 144 (12), 4605-4619, 2016	20	2016
Boosting association rule mining in large datasets via Gibbs sampling G Qian, CR Rao, X Sun, Y Wu Proceedings of the National Academy of Sciences 113 (18), 4958-4963, 2016	18	2016
A procedure for estimating the number of clusters in logistic regression clustering G Qian, Y Wu, Q Shao Journal of classification 26, 183-199, 2009	18	2009
Bayesian grouped horseshoe regression with application to additive models Z Xu, DF Schmidt, E Makalic, G Qian, JL Hopper AI 2016: Advances in Artificial Intelligence: 29th Australasian Joint …, 2016	16	2016
Modeling big spatio-temporal geo-hazards data for forecasting by error-correction cointegration and dimension-reduction H Wang, G Qian, A Tordesillas Spatial Statistics 36, 100432, 2020	14	2020
Estimation and selection in regression clustering G Qian, Y Wu European Journal of Pure and Applied Mathematics 4 (4), 455-466, 2011	14	2011
Strong limit theorems on model selection in generalized linear regression with binomial responses G Qian, Y Wu Statistica Sinica, 1335-1365, 2006	13	2006

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