BAyesian Model-Building Interface (Bambi) in Python.

an R package for structural equation modeling and more

rstanarm R package for Bayesian applied regression modeling

An R package for Bayesian structural equation modeling

Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models

Basic statistical modelling examples.

The official implementation of "Joint Modeling of Image and Label Statistics for Enhancing Model Generalizability of Medical Image Segmentation" via Pytorch

Learn about Probabilistic Time Series Forecasting, its key techniques, real-world applications, and advantages over traditional forecasting methods.

Code and resources to serve as a starting point for data science projects.

Recursive Partitioning for Structural Equation Models

農研機構統計研修「ベイズ統計モデリングとMCMC」

We present here a 1D convolutional neural network model to predict grain protein content using spectroscopic data of multiple cereals

OCaml Random Forests

rstanarm R package for Bayesian applied regression modeling

An autoencoder neural network and a Gaussian mixture model are used for generating movement quality scores for rehabilitation exercises.

Simulation Methods in Econometrics: Theory and Applications in MATLAB is an open-source textbook that aims to bridge the gap between econometric theory and the practical use of simulation techniques. It emphasizes intuition, reproducibility, and accessibility.

An R package implementing Principal Component Pursuit for pattern recognition in environmental health.

Expand broom::tidy() output for categorical parameter estimates

Portfolio of personal projects & curriculum from Springboard