Most of the models are completed in a single file and implemented in a simple way. The machine learning part of the code does not use any external libraries, except for the loading part of the ONNX ...

Multilevel modelling has rapidly become established as the appropriate tool for modelling data with complex hierarchical structures. It is important for extending our understanding of social, ...

What is a Gaussian Graphical Model ? A Gaussian graphical model captures conditional (in)dependencies among a set of variables. These are pairwise relations (partial correlations) controlling for the ...

remove-circle Internet Archive's in-browser bookreader "theater" requires JavaScript to be enabled. It appears your browser does not have it turned on. Please see ...

With the increase in artificial intelligence in real-world applications, there is interest in building hybrid systems that take both human and machine predictions into account. Previous work has shown ...

Modeling species distributions over space and time is one of the major research topics in both ecology and conservation biology. Joint Species Distribution models (JSDMs) have recently been introduced ...

The analysis of factor structures is one of the most critical psychometric applications. Frequently, variables (i.e., items or indicators) resulting from questionnaires using ordinal items with 2–7 ...

Telehealth services have the potential to improve access to care, especially in rural or urban areas with scarce health care resources. Despite the potential benefits, telehealth has not been fully ...

The cued-trials task-switching paradigm is used to investigate the processes involved in preparation to change task. Task switch trials typically show poorer performance than task repeat trials, ...

The dependent variable in this probit model is individuals’ survival. Survival takes a value of 1. Coefficients are in roman type, z statistics are in italics, and marginal effects are in bold.