Time Series Forecasting Practices and Mini-Projects

Forecasting Models: ARIMA, SARIMA, Exponential Smoothing, VARIMA, VARIMAX etc...
Preprocessing: Handling missing data, outliers, and seasonal adjustments

This repository is regularly updated with new techniques and experiments.
Contributions and feedback are welcome!

Name		Name	Last commit message	Last commit date
Latest commit History 43 Commits
.github		.github
ACF and PACF Plots		ACF and PACF Plots
ADF, KPSS Stationarity Test		ADF, KPSS Stationarity Test
AIC BIC Model Comparison		AIC BIC Model Comparison
ARIMA (AutoRegressive Integrated Moving Average Model)		ARIMA (AutoRegressive Integrated Moving Average Model)
ARMA (Auto-Regressive Moving Average Model)		ARMA (Auto-Regressive Moving Average Model)
Auto-Regressive Model		Auto-Regressive Model
Classical Decomposition		Classical Decomposition
Imputation, Interpolation, Predictive Modelling - PreProcessing Time Series		Imputation, Interpolation, Predictive Modelling - PreProcessing Time Series
KS Test		KS Test
Making Data Stationary		Making Data Stationary
Moving Average Model (MA)		Moving Average Model (MA)
Resampling - Preprocessing Time Series		Resampling - Preprocessing Time Series
SARIMA (Seasonal AutoRegressive Integrated Moving Average Model)		SARIMA (Seasonal AutoRegressive Integrated Moving Average Model)
STL Decomposition		STL Decomposition
Smoothing Methods		Smoothing Methods
VAR (Vector AutoRegressive Model)		VAR (Vector AutoRegressive Model)
VARIMA (Vector AutoRegressive Integrated Moving Average Model)		VARIMA (Vector AutoRegressive Integrated Moving Average Model)
VMA (Vector Moving Average Model)		VMA (Vector Moving Average Model)
White Noise and Random Walk Test		White Noise and Random Walk Test
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md

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