Abstract: The Conditional Expectation Function (CEF) is an optimal estimator in real space. Artificial Neural Networks (ANN), as the current state-of-the-art method, lack interpretability. Estimating ...

We consider a general non-parametric regression model, where the distribution of the error, given the covariate, is modelled by a conditional distribution function. For the estimation, a kernel ...

Envelope models represent a significant advancement in multivariate regression analysis, offering an efficient dimension reduction tool that enhances both estimation precision and predictive ...

Random effects logistic regression models are often used to model clustered binary response data. Regression parameters in these models have a conditional, subject-specific interpretation in that they ...

The goal of rbounds is to estimate bounds on the location of parameters in models in which the value of the parameter can only be partially identified. The package was developed to estimate the ...