AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
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 ...
SciELO

AgroReg: main regression models in agricultural sciences implemented as an R Package

Regression analysis is highly relevant to agricultural sciences since many of the factors studied are quantitative. Researchers have generally used polynomial models to explain their experimental ...
PNAS

Comparing variable selection and model averaging methods for logistic regression

Logistic regression is a statistical method used to model binary outcome variables, such as whether a patient recovers or not, using a set of predictors. There are many competing methods for ...
GitHub

Fortran Statistics and Machine Learning

FSML (Fortran Statistics and Machine Learning) is a scientific toolkit consisting of common statistical and machine learning procedures, including basic statistics (e.g., mean, variance, correlation), ...
Simon Fraser University

Lesson 10 Multiple Linear Regression

The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9. I will start with a ...