Scientific Research Publishing

A Bayesian-Inspired Framework for Parameter Estimation and Error Quantification ()

1 Dual Analytics, Geistthal-Södingberg, Austria. 2 Chair of Mathematics and Statistics, Montanuniversität Leoben, Leoben, Austria. 3 Materials Center Leoben Forschung GmbH, Leoben, Austria. 4 ...
GitHub

Biogeme is an open source freeware designed for the maximum likelihood estimation of parametric models in general, with a special emphasis on discrete choice models.

Biogeme requires Python >= 3.10 and can be installed from PyPI. pip install biogeme Installing Biogeme from source can be done after cloning the repository with the ...
Frontiers

A likelihood ratio framework for inferring close kinship from dynamically selected SNPs

Forensic genetic genealogy (FGG) is a force-multiplier for human identification, leveraging dense single nucleotide polymorphism (SNP) data to infer relationships through identity by descent (IBD) ...
GitHub

PyJSD: Python implementation of the Jensen-Shannon divergence

This Python module implements estimation of the JSD scores for the observed data assuming some distribution. This module was developed when performing empirical analysis for the forthcomming paper by ...
C&EN

MOFSynth: A Computational Tool toward Synthetic Likelihood Predictions of MOFs

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In the past decade, high-throughput computational studies of materials have increased ...
IEEE

A Python Code For Maximum Likelihood Estimation Of The Location And Scale Parameters Of The Truncated Normal Distribution

Abstract: Extracellular neural recordings obtained from chronically implanted microelectrode arrays are widely used in behavioral neurophysiology and invasive brain-machine interfaces. After the raw ...