A statistics package with a variety of bootstrap and other resampling tools. This repository is synced to the same-named repository owned by GNU-Octave. It exists to facilitate publication of the developmental version of the statistics-resampling toolbox at MathWorks FileExchange.

Business intelligence analyzer - Supermarket sales.

This is a warehouse for DLinear-Pytorch-model, can be used to train your text dataset for time series forecasting tasks.

Spells for everyday living. (also a book coming out in 2024)

OLS Linear Model - Regressing User Beer Ratings based on Observations

Linear models with Stan and Pandas

fitting a linear regression on the height and the bolting time of the lettuce phenotypes to see if there can be a linear regression to be established

This is my senior project for my data science degree at Belmont University where I will be looking at the effect of the MLB Pitch Clock on pitcher's performance.

tldr; If you have a 2-4GB dataset and you need to estimate a (generalized) linear model with a large number of fixed effects, this package is for you.

Package offers simultaneous regression and binary classification especially for educational data

A matlab suite for Psycho-Physiological Modelling

Code for predicting the severity of earthquake impact on buildings through various experiments, utilizing models like Logistic Regression, SVM, XGBoost, Neural Networks, and Random Classifier. It employs Grid Search and Randomized Search for optimal configuration and relies on feature correlations as primary predictors, adjustable with a threshold.

Interpretable and efficient predictors using pre-trained language models. Scikit-learn compatible.

Inferring patient-specific regulatory alterations

Additional linear models including instrumental variable and panel data models that are missing from statsmodels.

📖An interactive companion to the well-received textbook 'Introduction to Econometrics' by Stock & Watson (2015)

GAMLj: GLM, Mixed, Generalized and Generalized mixed models for jamovi

Generates and evaluates D, I, A, Alias, E, T, G, and custom optimal designs. Supports generation and evaluation of mixture and split/split-split/N-split plot designs. Includes parametric and Monte Carlo power evaluation functions. Provides a framework to evaluate power using functions provided in other packages or written by the user.

This Python script conducts various data processing, visualization, and modeling tasks on a dataset.

Project on investigating opportunities to decrease customer churn and increase profitability for a telecom company.