GitHub

Tigramite – Causal inference for time series datasets

Update: Tigramite now has a new CausalEffects class that allows to estimate (conditional) causal effects and mediation based on assuming a causal graph. Have a look at the tutorial. Further, Tigramite ...
IEEE

Methodology for the Evaluation of Linear Response Microwave Sensors

Abstract: Most microwave sensors establish a relationship between electrical parameters or dielectric properties with the property of interest of a sample using simple linear regression to make ...
GitHub

HLR - Hierarchical Linear Regression in Python

It is built to work with Pandas dataframes, uses SciPy, statsmodels and pingouin under the hood, and runs diagnostic tests for testing assumptions while plotting figures with matplotlib and seaborn.
Visual Studio Magazine

Gaussian Process Regression Using the scikit Library

A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, age, number of bedrooms and ...
C&EN

Pairwise Difference Regression: A Machine Learning Meta-algorithm for Improved Prediction and Uncertainty Quantification in Chemical Search

Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United ...
Frontiers

Machine learning for neuroimaging with scikit-learn

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of ...