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academic-website

Repo for academic style website

brand-public_repo

Public repo for BRAND: Bayesian Robust Adaptive Novelty Detector. A two-stage Bayesian Nonparametric model for novelty detection with robust prior information.

cwrmmonitor

R package providing graphical and computational tools to guide parameter choice for the cluster weighted robust model. Associated paper Cappozzo, Garcìa Escudero, Greselin, Mayo-Iscar (2022+) Graphical and computational tools to guide parameter choice for the cluster weighted robust model.

emlmm

R package for fitting penalised linear mixed-effect models via EM-type algorithms

erum2018

"Building a package that lasts" — eRum 2018 workshop

erum2020program

e-Rum2020 program and materials

intrinsic

Public repository for the R package intRinsic

labs_nps_ay_2022_2023

Nonparametric statistics POLIMI AY 2022/2023: lab notebooks

lsgl

Multivariate Linear Sparse Group Lasso

mattransmix

:exclamation: This is a read-only mirror of the CRAN R package repository. MatTransMix — Clustering with Matrix Gaussian and Matrix Transformation Mixture Models

mixedelnet

An R package for fitting high dimensional linear mixed-effects models with elastic-net penalty

netreg

:bar_chart: Generalized linear regression models with network-regularization in R.

parfm

:exclamation: This is a read-only mirror of the CRAN R package repository. parfm — Parametric Frailty Models

quarto-web

Quarto website

raedda

Model-based framework for robust classification that jointly accounts for outliers, label noise and unobserved classes in the test set.

reticulate

R Interface to Python

rstudio-conf-2018

Slide, code and data for "Applied Machine Learning" at Rstudio-conf 2018

rupclass

Robust model-based classification based on trimming and constraints

sparsemix

sparsemixmat

stats-monitoring_cwrm

This repository is associated with the paper Cappozzo, Garcìa Escudero, Greselin, Mayo-Iscar (2021) Parameter choice, stability and validity for robust cluster weighted modeling.

tlemix

Trimmed Maximum Likelihood Estimation

varselemst

Robust variable selection for REDDA models via EMST algorithm

varseltbic

Robust variable selection for REDDA models via TBIC approximation to the integrated likelihood. It is a robust adaptation of the greedy forward search algorithm for discriminant analysis. Based on clustvarsel R package.

vistime

Pretty timelines in R.