Luca Scrucca

Luca Scrucca

Associate Professor of Statistics

Università degli Studi di Perugia

About me

I’m an applied statistician. In a qq broader sense, I’m also a data scientist because I do data analysis, and I do research on the methodology and computational aspects of data analysis. I’m an enthusiastic R user and package developer.

I’m also serving as Associate Editor for Journal of Statistical Software and Statistics and Computing.

Interests
  • Mixture models
  • Model-based clustering and classification
  • Statistical learning
  • Dimension reduction methods and regression graphics
  • Genetic and evolutionary algorithms
Education
  • PhD in Statistics, 2000

    Università degli Studi di Perugia

  • MSc Statistics, 2000

    University of Minnesota

Research

Academic publications

Book

Scrucca L., Fraley C., Murphy T. B. and Raftery A. E. (2023) Model-Based Clustering, Classification, and Density Estimation Using mclust in R, Chapman & Hall/CRC, ISBN: 978-1032234953.
Companion book website

Recent publications


(2023). Mixture-based estimation of entropy. Computational Statistics & Data Analysis, 177, 107582.

PDF DOI

(2022). Modal clustering on PPGMMGA projection subspace. Australian & New Zealand Journal of Statistics, 64:2, 158–170.

PDF DOI

(2021). A fast and efficient Modal EM algorithm for Gaussian mixtures. Statistical Analysis and Data Mining, 14:4, 305–314.

PDF DOI

(2019). Projection pursuit based on Gaussian mixtures and evolutionary algorithms. Journal of Computational and Graphical Statistics, 28:4, 847–860.

PDF DOI

Software

R packages and functions

I’m the author and/or maintainer of several packages and functions written in R, a free software environment for statistical computing and graphics, using RStudio, an integrated development environment (IDE) for R.

   A collection of R packages for statistical modeling using Gaussian mixtures.

   List of R packages and functions.

Teaching

Courses list


Contact