Work

On a Low-Rank Matrix Single-Index Model

Year: 2023

Type: article

Abstract: In this paper, we conduct a theoretical examination of a low-rank matrix single-index model. This model has recently been introduced in the field of biostatistics, but its theoretical properties for jointly estimating the link function and the coefficient matrix have not yet been fully explored. In this paper, we make use of the PAC-Bayesian bounds technique to provide a thorough theoretical understanding of the joint estimation of the link function and the coefficient matrix. This allows us to gain a deeper insight into the properties of this model and its potential applications in different fields.

Source: Mathematics

DOI: 10.3390/math11092065

Author: The Tien Mai

Institution: Norwegian University of Science and Technology

Language: English

Topic: Statistical Methods and Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,336

Funder: Norges Forskningsråd