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Luca Scrucca
Luca Scrucca
Associate Professor of Statistics, University of Perugia, Italy
Verified email at unipg.it - Homepage
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Cited by
Cited by
Year
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
25732016
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
11372012
GA: A package for genetic algorithms in R
L Scrucca
Journal of Statistical Software 53, 1-37, 2013
8582013
Competing risk analysis using R: an easy guide for clinicians
L Scrucca, A Santucci, F Aversa
Bone marrow transplantation 40 (4), 381-387, 2007
7222007
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
4712010
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
393*2006
qcc: an R package for quality control charting and statistical process control
L Scrucca
R News 4 (1), 11--17, 2004
2872004
On some extensions to GA package: hybrid optimisation, parallelisation and islands evolution
L Scrucca
arXiv preprint arXiv:1605.01931, 2016
1242016
mclust Version 4 for R: normal mixture modeling for model-based clustering, classification, and density estimation. Department of Statistics, University of Washington
C Fraley, AE Raftery, TB Murphy, L Scrucca
Washington: University of Washington, 2012
892012
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, 167967, 2016
822016
Dimension reduction for model-based clustering
L Scrucca
Statistics and Computing 20, 471-484, 2010
802010
Improved initialisation of model-based clustering using Gaussian hierarchical partitions
L Scrucca, AE Raftery
Advances in data analysis and classification 9, 447-460, 2015
702015
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
692017
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
682003
mclust: Normal mixture modeling for model-based clustering, classification, and density estimation
C Fraley, AE Raftery, L Scrucca
662012
clustvarsel: a package implementing variable selection for Gaussian model-based clustering in R
L Scrucca, AE Raftery
Journal of Statistical Software 84, 2018
642018
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
632016
Model-based SIR for dimension reduction
L Scrucca
Computational Statistics & Data Analysis 55 (11), 3010-3026, 2011
562011
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
50*2019
Clustering multivariate spatial data based on local measures of spatial autocorrelation
L Scrucca
Quaderni del Dipartimento di Economia, Finanza e Statistica 20 (1), 11, 2005
492005
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