Package for analyzing GWAS summary statistics data
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Updated
Jun 26, 2024 - Julia
Package for analyzing GWAS summary statistics data
Methods for selecting diverse (molecular) database.
Variable Selection with Knockoffs
Developer Version of the R package CAST: Caret Applications for Spatio-Temporal models
Efficient Variable Selection for GLMs in R
Projection predictive variable selection
R package for estimating copula entropy (mutual information), transfer entropy (conditional mutual information), and the statistic for multivariate normality test and two-sample test
Variable Selection Network with PyTorch
Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test, and change point detection in Python
The goal of the project is to predict Life Expectancy using various factors and to determine the relationship that exists between them.
🧲 Multi-step adaptive estimation for reducing false positive selection in sparse regressions
R package for fitting semiparametric accelerated failure time models in high dimensions
Boosting Functional Regression Models. The current release version can be found on CRAN (http://cran.r-project.org/package=FDboost).
📈 Ordered Homogeneity Pursuit Lasso for Group Variable Selection
A novel meta-analysis framework of the R-squared (R2)-based mediation effect estimation for high-dimensional omics mediators
BAS R package https://merliseclyde.github.io/BAS/
OmicSelector - Environment, docker-based application and R package for biomarker signiture selection (feature selection) & deep learning diagnostic tool development from high-throughput high-throughput omics experiments and other multidimensional datasets. Initially developed for miRNA-seq, RNA-seq and qPCR.
Linear Model Interaction Terms Optimizer
Performs Variables selection and model tuning for Species Distribution Models (SDMs). It provides also several utilities to display results.
Practices and Assignments from the Data Analysis and Regression Class
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