74 citations · 277 across the 20 of their papers we have counts for
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stat.CO2016★ 74 cited
On some extensions to GA package: hybrid optimisation, parallelisation and islands evolution
Luca Scrucca
Genetic algorithms are stochastic iterative algorithms in which a population of individuals evolve by emulating the process of biological evolution and natural selection. The R pac…
stat.CO2015★ 2 cited
Investigation of Parameter Uncertainty in Clustering Using a Gaussian Mixture Model Via Jackknife, Bootstrap and Weighted Likelihood Bootstrap
Adrian O'Hagan, Thomas Brendan Murphy, Luca Scrucca +1
Mixture models are a popular tool in model-based clustering. Such a model is often fitted by a procedure that maximizes the likelihood, such as the EM algorithm. At convergence, th…
stat.CO2014★ 22 cited
clustvarsel: A Package Implementing Variable Selection for Model-based Clustering in R
Luca Scrucca, Adrian E. Raftery
Finite mixture modelling provides a framework for cluster analysis based on parsimonious Gaussian mixture models. Variable or feature selection is of particular importance in situa…