[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"
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Updated
Jan 27, 2024 - Python
[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"
📖An interactive companion to the well-received textbook 'Introduction to Econometrics' by Stock & Watson (2015)
Additional linear models including instrumental variable and panel data models that are missing from statsmodels.
📊 Methods of Applied Statistics Course Textbook Repository
A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard.
Linear, IV and GMM Regressions With Any Number of Fixed Effects
A python library to build Model Trees with Linear Models at the leaves.
An R Port of Stata's 'margins' Command
📦 BRoadly Useful Convenient and Efficient R functions that BRing Users Concise and Elegant R data analyses.
Input Output Hidden Markov Model (IOHMM) in Python
Lp modeler written in Rust
Python port of "Common statistical tests are linear models" by Jonas Kristoffer Lindeløv.
Tools for developing OLS regression models
Machine Learning C++
ICDSS Machine Learning Workshop Series: Linear Models
Linear Models With R and Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models - by J Faraway
🎓 Tidy tools for academics
This repository contains R code for exercices and plots in the famous book.
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.
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