statistical-modeling

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

Basic statistical modelling examples.

農研機構統計研修「ベイズ統計モデリングとMCMC」

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

OCaml Random Forests

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

Wrapper on top of libsvm-tools

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

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

Created a model to estimate the measurement error existing in ROC curves - Measurement Error model, Bernstein polynomial Model, Contaminated Non-parametric Density Estimation, MLE, EM Algorithm, R

rstanarm R package for Bayesian applied regression modeling

The Github Page of InPhyT.

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

Portfolio of personal projects & curriculum from Springboard

Simple statistical prediction of the survival chances of the passengers in the testing set, given certain conditions as input. Refer to README.md for more detail

In this project, I web scraped and parsed listing available high-rated apartments within 2 miles around Boston Univeristy Center from apartments.com, analyzed price, vacancy, special promotions against different room types, and discovered the price and availability trends in 2021.

RStudio project utilizing various statistical methods to replicate and diagnose the findings of Appel and Loyle from their study on post-conflict justice and foreign direct investment.

Statsmodels: statistical modeling and econometrics in Python

MATH-342 Time Series course taken at EPFL during Spring 17-18.

[Built during technical internship at SAS Institute, May 2016 - Aug 2016] Created automated skin cancer detection software using image analysis, feature extraction, and statistical modeling that analyzes images of skin lesions to detect possibly cancerous growths. Presented research and algorithms at the international JMP Discovery Summit (also selected as Best Student Poster), to the Women in Data Science Meetup, at the JMP Developers' Meeting, and at the SAS Intern Expo.

A Survey on ML Techniques for Airbnb Price Prediction

A new way to analyse computer mouse trajectories

Forecast the demand for each product in the next month for a group of Walmart stores, using statistical modeling (ETS) and machine learning (LGBM, XGBoost, RandomForest). This is a team project contributed by Leyli Ramazanova, Sviatlana Yasiukova, Simone Genetin, and myself.

Small examples on how to jump into statistical modelling in C++

The interface library for probabilistic modeling in HEP

Automatically determine trends, correlations, and feature selections given dataset(s)

This is a data analysis code in which you can find chi squared and kolmogorov smirnov agorithms implemented

Toy examples of how to utilise Rcpp interface to pass the data from R to C++ and call the procedures useful for statistical modelling within. 📚