Speaker : Michail Tsagris, Associate Prof., Department of Economics, University of Crete
Date : 21-02-2025
Time: 11:00 - 12:30
Location : Payatakes Seminar Room - FORTH, Main Building, 1st floor
Title : Constrained least squares simplicial-simplicial regression
Abstract:
Simplicial-simplicial regression refers to the regression setting where both the responses and predictor variables lie within the simplex space, i.e. they are compositional. For this setting, constrained least squares, where the regression coefficients themselves lie within the simplex, is proposed. The model is transformation-free but the adoption of a power transformation is straightforward, it can treat more than one compositional datasets as predictors and offers the possibility of weights among the simplicial predictors. Among the model’s advantages are its ability to treat zeros in a natural way and a highly computationally efficient algorithm to estimate its coefficients. Resampling based hypothesis testing procedures are employed regarding inference, such as linear independence, and equality of the regression coefficients to some pre-specified values. The strategy behind the formulation of the new model implemented is related to an existing methodology, that is of the same spirit, showcasing how other similar models can be employed as well. Finally, the performance of the proposed technique and its comparison to the existing methodology takes place using simulation studies and real data examples.
Bio:
Michail Tsagris is an Associate Professor at the Department of Economics of the University of Crete (UoC) and an Adjunct Professor in the Department of Mathematics and Statistics at the University of New Brunswick Saint John. Prior to these he worked as a Teaching Fellow and then as an Assistant Professor at the Department of Economics (UoC), as a Research Associate at the Department of Computer Science (UoC), as an Assistant Professor at the American University of the Middle East (Kuwait) and as a Research Associate at the School of Mathematical Sciences of the University of Nottingham. He received his BSc and MSc in statistics from the Athens University of Economics and Business (Greece) and his PhD in statistics from the University of Nottingham. Michail has published more than 60 papers in journals, conference proceedings and book chapters and has (co-)developed 40 R packages. His current research interests include computational statistics, compositional and directional data analysis, applied econometrics and machine learning. His research span the fields of multivariate statistics, hypothesis testing, variable selection, directional data, and quantitative methods in economics.
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