partial-least-squares

PLS for Big Data: A unified parallel algorithm for regularised group PLS

Pierre Lafaye de Micheaux, Benoit Liquet, Matt Sutton / 2021-01-28

We look at the problem of learning latent structure between two blocks of data through the partial least squares (PLS) approach. These methods include approaches for supervised and unsupervised statistical learning. We review these methods and present approaches to decrease the computation time and…

machine-learning

Machine learning for causal inference that works

Richard Hahn / 2021-01-26

I’ve kindly been invited to share a few words about a recent paper my colleagues and I published in Bayesian Analysis: “Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects”. In that paper, we motivate and describe a method that we call…

classification

The Multiple Latent Block Model for mixed data

Margot Selosse, Julien Jacques, Christophe Biernacki / 2021-01-05

Co-clustering techniques, which group observations and features simultaneously, have proven to be efficient in summarising data sets. They exploit the dualism between rows and columns and the data set is summarized in blocks (the crossing of a row-cluster and a column-cluster). However, in the case…

causal-inference

Causal discovery in the presence of discrete latent variables

Rune Christiansen and Jonas Peters / 2020-12-15

We address the problem of causal structure learning in the presence of hidden variables. Given a target variable and a vector of covariates, we are trying to infer the set of observable causal parents of the target variable. There are many good reasons for being interested in causal predictors.…

Functional-Data-Analysis

Functional Regression Control Chart: a New Framework for Profile Monitoring

Fabio Centofanti, Antonio Lepore, Alessandra Menafoglio, Biagio Palumbo, and Simone Vantini / 2020-12-04

New statistical process control (SPC) methods have to be developed in order to handle more and more complex data, which are available because of the advent of new data acquisition technologies. In particular, in many practical situations the quality characteristic of a process can be modelled as a…

economic statistics

Online cash register data in the measurement of retail trade turnover

Ábel Csékus / 2020-12-03

The Hungarian Central Statistical Office uses online cash register data for the measurement of retail trade and food services. The data source allows the statistical office to considerably cut administrative burden of data providers without quality loss in retail trade statistics. Online cash…