Forecasting Functions for Time Series and Linear Models

Data, Benchmarks, and methods submitted to the M4 forecasting competition

Time series features

An R package that makes xgboost models fully interpretable

A set of tools to understand what is happening inside a Random Forest

Hierarchical and Grouped Time Series

Tools for developing OLS regression models

Extension package of linear regression diagonostic plots in ggplot2.

GRATIS: GeneRAting TIme Series with diverse and controllable characteristics

demography package for R

This repository contains the experiments related with a new baseline model that can be used in forecasting weekly time series. This model uses the forecasts of 4 sub-models: TBATS, Theta, Dynamic H…

Temporal HIErarchical Forecasting

The R package M4comp2018 contains the 100000 time series from the M4-competition (https://www.m4.unic.ac.cy/)

Variable Selection Using Random Forests

sgmcmc: a stochastic gradient MCMC package for R

An implementation of the Heterogeneous AutoRegressive model from Corsi(2009)

Using stochastic gradient descent (SGD) with explicit and implicit updates to fit large-scale statistical models.

Course materials for BANA 7052 (Applied Linear Regression) at UC

MOSS: Multi-Omic integration via Sparse Singular Decomposition

M5 Competition Data

Covariate-dependent copula models

Methods used for producing product sales probabilistic forecasting (statistical methods, ML models, theoretical estimations, and empirical approaches)