Takip et
Luca Scrucca
Luca Scrucca
Full Professor of Statistics, University of Bologna, Italy
unibo.it üzerinde doğrulanmış e-posta adresine sahip - Ana Sayfa
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
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
30552016
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
12662012
GA: A package for genetic algorithms in R
L Scrucca
Journal of Statistical Software 53, 1-37, 2013
9892013
Competing risk analysis using R: an easy guide for clinicians
L Scrucca, A Santucci, F Aversa
Bone marrow transplantation 40 (4), 381-387, 2007
7662007
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
5002010
qcc: an R package for quality control charting and statistical process control
L Scrucca
R News 4 (1), 11--17, 2004
3182004
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
292*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
1692023
On some extensions to GA package: hybrid optimisation, parallelisation and islands evolution
L Scrucca
arXiv preprint arXiv:1605.01931, 2016
1522016
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
1042016
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
1022018
Dimension reduction for model-based clustering
L Scrucca
Statistics and Computing 20, 471-484, 2010
902010
Improved initialisation of model-based clustering using Gaussian hierarchical partitions
L Scrucca, AE Raftery
Advances in data analysis and classification 9, 447-460, 2015
832015
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
762003
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
752017
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
732016
mclust: Normal mixture modeling for model-based clustering, classification, and density estimation
C Fraley, AE Raftery, L Scrucca
662012
Model-based SIR for dimension reduction
L Scrucca
Computational Statistics & Data Analysis 55 (11), 3010-3026, 2011
642011
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
612019
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
612016
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