This tutorial is supplementary to the manuscript Bayesian metamodeling of complex biological systems across varying representations. Metamodeling is an unique probabilistic framework that may couple ...

This tutorial summarizes details of the Bayesian Joint spike-and-slab Graphical Lasso (SSJGL) algorithm (Li et. al 2019), then walks through the steps needed to run the spikeyglass package using a ...

When evaluating cognitive models based on fits to observed data (or, really, any model that has free parameters), parameter estimation is critically important. Traditional techniques like hill ...

Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain Monte-Carlo ...

In the field of cognitive psychology, the p-value hypothesis test has established a stranglehold on statistical reporting. This is unfortunate, as the p-value provides at best a rough estimate of the ...

1 Department of Psychology, University of Oklahoma, Norman, OK, United States 2 Department of Psychology, University of Virginia, Charlottesville, VA, United States InsVs play an instrumental role in ...

Researchers in numerical cognition rely on hypothesis testing and parameter estimation to evaluate the evidential value of data. Though there has been increased interest in Bayesian statistics as an ...

ABSTRACT: Soil-water characteristic curve (SWCC) is significant to estimate the site-specific unsaturated soil properties (such as unsaturated shear strength and coefficient of permeability) for ...