APLR builds predictive, interpretable regression and classification models using Automatic Piecewise Linear Regression. It often rivals tree-based methods in predictive accuracy while offering ...

{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for multivariate modeling and forecasting ...

The analysis of multi-environment trials (MET) data in plant breeding and agricultural research is inherently challenging, with conventional ANOVA-based methods exhibiting limitations as the ...

(a) General location of the study site. (b ... creating simulation data from the testing set, training the model using the original training set, testing the model on the simulated testing and ...

This course provides an introduction to principles, terminology, and strategies for statistical modelling with the linear model as initial framework for data analysis. The linear model is a modelling ...

Here, we report the emergence of a linear scaling law in this complicated random system. We derived an accurate statistical high-order limit model and found that the model remains the same when the ...

generalized linear models, and group families. Finally, basic results of higher-order asymptotics are introduced (index notation, asymptotic expansions for statistics and distributions, and major ...

Additionally, we extend our analysis to more general classifiers and datasets ... We present a unified likelihood ratio-based confidence sequence (CS) for any (self-concordant) generalized linear ...

It is time to return to the traditional values of a circular economy. Our current linear approach is proving to be ...

NVIDIA announces the general availability of its Secure AI solution, focusing on protecting large language models with enhanced security features. NVIDIA has officially announced the general ...