Luca Scrucca

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Adrian E. RafteryProfessor of Statistics and Sociology, University of WashingtonVerified email at uw.edu
Brendan MurphyUniversity College DublinVerified email at ucd.ie
Michael FopLecturer/Assistant Professor University College DublinVerified email at ucd.ie
Cecilia ChirieleisonAssociate Professor of Business Administration, University of PerugiaVerified email at unipg.it
Baljinder K. SahdraAssociate Professor, Institute for Positive Psychology and Education, ACUVerified email at acu.edu.au
Alessio SerafiniData Reply IT srlVerified email at unipg.it
Isobel Claire GormleyProfessor, School of Mathematics and Statistics, University College DublinVerified email at ucd.ie
Anthony O'HaganEmeritus Professor, the University of SheffieldVerified email at sheffield.ac.uk
Joseph CiarrochiProfessor, Institute of Positive Psychology and Education, Australian Catholic UniversityVerified email at acu.edu.au
Philip D ParkerInstitute of Positive Psychology and Education - Australian Catholic UniversityVerified email at acu.edu.au
Giovanna MenardiDepartment of Statistical Science, University of PaduaVerified email at stat.unipd.it
Roberto Cirocchi.Associate Professor of Surgery, University of PerugiaVerified email at unipg.it
Paul D. McNicholasProfessor & Canada Research Chair, McMaster University, Ontario, CanadaVerified email at math.mcmaster.ca
Sanford WeisbergProfessor of Statistics, University of MinnesotaVerified email at umn.edu
Nema DeanQ-step Reader in Statistics, University of GlasgowVerified email at glasgow.ac.uk
Stéphane ROBINSorbonne universitéVerified email at sorbonne-universite.fr
Corrado CencettiProfessore ordinario di Geologia Applicata, Università di PerugiaVerified email at unipg.it
pierluigi de rosaPostDoc, University of PerugiaVerified email at unipg.it
Avner Bar-HenCNAMVerified email at cnam.fr
Dilhari T. AttygalleSenior Lecturer, University of ColomboVerified email at stat.cmb.ac.lk

Luca Scrucca

Full Professor of Statistics, University of Bologna, Italy

Verified email at unibo.it - Homepage

Computational Statistics Mixture models Model-based clustering Classification Genetic Algorithms


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mclust 5: clustering, classification and density estimation using Gaussian finite mixture models L Scrucca, M Fop, TB Murphy, AE Raftery The R journal 8 (1), 289, 2016	3017	2016
mclust version 4 for R: normal mixture modeling for model-based clustering, classification, and density estimation C Fraley, AE Raftery, TB Murphy, L Scrucca Technical report 597, 1, 2012	1264	2012
GA: A package for genetic algorithms in R L Scrucca Journal of Statistical Software 53, 1-37, 2013	978	2013
Competing risk analysis using R: an easy guide for clinicians L Scrucca, A Santucci, F Aversa Bone marrow transplantation 40 (4), 381-387, 2007	762	2007
Regression modeling of competing risk using R: an in depth guide for clinicians L Scrucca, A Santucci, F Aversa Bone marrow transplantation 45 (9), 1388-1395, 2010	497	2010
qcc: an R package for quality control charting and statistical process control L Scrucca R News 4 (1), 11--17, 2004	315	2004
MCLUST version 3: an R package for normal mixture modeling and model-based clustering C Fraley, AE Raftery WASHINGTON UNIV SEATTLE DEPT OF STATISTICS, 2006	289*	2006
Model-based clustering, classification, and density estimation using mclust in R L Scrucca, C Fraley, TB Murphy, AE Raftery Chapman and Hall/CRC, 2023	156	2023
On some extensions to GA package: hybrid optimisation, parallelisation and islands evolution L Scrucca arXiv preprint arXiv:1605.01931, 2016	149	2016
Using genetic algorithms in a large nationally representative American sample to abbreviate the Multidimensional Experiential Avoidance Questionnaire BK Sahdra, J Ciarrochi, P Parker, L Scrucca Frontiers in Psychology 7, 189, 2016	103	2016
clustvarsel: A package implementing variable selection for Gaussian model-based clustering in R L Scrucca, AE Raftery Journal of Statistical Software 84, 1-28, 2018	102	2018
Dimension reduction for model-based clustering L Scrucca Statistics and Computing 20, 471-484, 2010	90	2010
Improved initialisation of model-based clustering using Gaussian hierarchical partitions L Scrucca, AE Raftery Advances in data analysis and classification 9, 447-460, 2015	82	2015
Robotic right hemicolectomy: analysis of 108 consecutive procedures and multidimensional assessment of the learning curve A Parisi, L Scrucca, J Desiderio, A Gemini, S Guarino, F Ricci, R Cirocchi, ... Surgical Oncology 26 (1), 28-36, 2017	75	2017
Prevalence of carotid stenosis in type 2 diabetic patients asymptomatic for cerebrovascular disease. M De Angelis, L Scrucca, M Leandri, S Mincigrucci, S Bistoni, M Bovi, ... Diabetes, nutrition & metabolism 16 (1), 48-55, 2003	75	2003
mclust: Gaussian mixture modelling for model-based clustering, classification, and density estimation C Fraley, AE Raftery, L Scrucca, TB Murphy, M Fop R package version 5 (2), 2016	72	2016
mclust: Normal mixture modeling for model-based clustering, classification, and density estimation C Fraley, AE Raftery, L Scrucca	66	2012
Model-based SIR for dimension reduction L Scrucca Computational Statistics & Data Analysis 55 (11), 3010-3026, 2011	64	2011
Investigation of parameter uncertainty in clustering using a Gaussian mixture model via jackknife, bootstrap and weighted likelihood bootstrap A O’Hagan, TB Murphy, L Scrucca, IC Gormley Computational Statistics 34 (4), 1779-1813, 2019	59*	2019
mclust 5: Clustering, classification and density estimation using Gaussian finite mixture models. The R Journal, 8 (1), 289–317 L Scrucca, M Fop, TB Murphy, AE Raftery DOI 10.32614/RJ-2016-021, 2016	59	2016

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