Time Series Forecasting

This repository is a personal project for a centralized documentation about the concepts and implementation examples of some of the most relevant methods and tools currently used for time series forecasting.

###Topics:

• Introduction to time series (TS)

  • Description of data structure, AC Plots
  • Component decomposition
  • Stationary propoerties, Dickey-Fuller test
  • Target transformations (Log, Cox-box)
  • Residuals
  • Metrics to measure forecasting performance

• Statistical Models

  • Univariate TS modelling: Average, Exponential smoothing, ARIMA models
  • Multivariate TS & External-regressors
  • Component-based TS modelling(tools): Facebook's Prophet, RSTL
  • Structural TS modelling: Hierarchical time series, Bayesian structural TS

• Machine Learning Models

  • (Linear) Regression models & standard toolbox (SVM, GBDT)
  • Hidden Markov Models
  • Seq2seq models
  • Recurrent NN (RNN,LSTM)

• Use Bayesian forecasting