Explore non-linear regression's role in data science and how it expands beyond linear models' capabilities for complex data analysis.

This study presents a relaxation method for second-order matrix-valued multivariate polynomial inequalities (SMMPI), with a specific application to the stability ...

This paper considers the problem of jointly decomposing a set of time series variables into cyclical and trend components, subject to sets of stochastic linear restrictions among these cyclical and ...

Learn how to build a multivariate linear regression model step by step—no libraries, just pure C++ logic!

This paper presents a procedure for analyzing a model in which the parameter vector has two parts: a finite-dimensional component θ and a nonparametric component λ. The procedure does not require ...

Multiple linear regression (MLR) is a statistical technique that uses several explanatory variables to predict the outcome of a response variable.

2.3 Multivariate linear regression models We aimed to create a global Multiple Input Single Output (MISO) linear regression model for the rough SF2 estimation, which allowed for treating the ...