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 ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

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 ...

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, ...

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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, ...

This article considers a methodology for flexibly characterizing the relationship between a response and multiple predictors. Goals are (1) to estimate the conditional response distribution addressing ...