The paper is concerned with parametric models for populations of curves; i. e. models of the form $y_{i}(x)=f(\boldsymbol{\theta}_{\mathbf{\mathit{i}}};x)$ + error, i ...

Fitting data with nonlinear regression -- Fitting data with linear regression -- Models -- How nonlinear regression works -- Confidence intervals of the parameters -- Comparing models -- How does a ...

This is a preview. Log in through your library . Abstract Many iterative regression methods only perform well near a solution. One may construct a modified problem with a free parameter (k), which has ...

This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...

Predictive modeling of data using modern regression and classification methods. Multiple linear regression; logistic regression; pitfalls and diagnostics; nonparametric and nonlinear regression and ...