Time series analysis

Last updated Nov 14, 2024 Edit Source

See:

• AI/Supervised Learning/Regression
• AI/Forecasting
• AI/Deep learning/RNNs
• AI/Deep learning/CNNs
• AI/Deep learning/DL
• AI/Deep learning/Transformers
• AI/Causality/Causality

• https://en.wikipedia.org/wiki/Time_series
• https://github.com/MaxBenChrist/awesome_time_series_in_python
• https://github.com/frutik/awesome-timeseries
• https://github.com/cuge1995/awesome-time-series
• http://machinelearningmastery.com/convert-time-series-supervised-learning-problem-python/
• Python to work with time series data

• See “Code” in AI/Forecasting
• #PAPER A systematic review of Python packages for time series analysis (Siebert 2021)
• #CODE tsai - State-of-the-art Deep Learning library for Time Series and Sequences
  • https://timeseriesai.github.io/tsai/
• #CODE Sktime
  • https://towardsdatascience.com/sktime-a-unified-python-library-for-time-series-machine-learning-3c103c139a55
• #CODE Stumpy - STUMPY is a powerful and scalable Python library for modern time series analysis
• #CODE Orbit - A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood
  • https://eng.uber.com/the-new-version-of-orbit-v1-1-is-released/
• #CODE TSflex
  • https://predict-idlab.github.io/tsflex/
• #CODE Merlion - Merlion is a Python library for time series intelligence
  • #PAPER Merlion: A Machine Learning Library for Time Series (Bhatnagar 2021)
• #CODE Kats
  • Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends
  • https://facebookresearch.github.io/Kats/
  • https://engineering.fb.com/2021/06/21/open-source/kats/
  • https://towardsdatascience.com/kats-a-generalizable-framework-to-analyze-time-series-data-in-python-3c8d21efe057
• #CODE Tsfresh - Time Series Feature extraction based on scalable hypothesis tests
  • Automatic extraction of relevant features from time series
• #CODE TSFEL
  • #PAPER TSFEL: Time Series Feature Extraction Library (Barandas 2020)
• #CODE Tslearn - A machine learning toolkit dedicated to time-series data
• #CODE Pmdarima
  • Pyramid bridges one more gap between R and Python by bringing R’s auto.arima to Python. Pyramid wraps statsmodels’ well-tested ARIMA and SARIMAX estimators.
• #CODE Tick
• #CODE Feature engine
• #CODE Featuretools - An open source python library for automated feature engineering
  • https://www.featuretools.com/

See AI/Forecasting

See AI/Anomaly and Outlier Detection

• Autoregressive
• Moving average
• Autoregressive moving average (ARMA)
• Autoregressive integrated moving average (ARIMA)
• Generalized additive model (GAM)
  • http://www.kdnuggets.com/2017/04/time-series-analysis-generalized-additive-models.html
• #PAPER HyperTime: Implicit Neural Representation for Time Series (Fons 2022)

• UEA & UCR Time Series Classification Repository
  • Datasets
• Dynamic time warping - DTW is one of the algorithms for measuring similarity between two temporal sequences, which may vary in speed
• https://medium.com/@hassanismailfawaz/deep-learning-for-time-series-classification-a-brief-overview-73b58767ed0f
• #PAPER ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels (Dempster 2019)
• #PAPER InceptionTime: Finding AlexNet for Time Series Classification (Ismail Fawaz 2019)
• #PAPER Deep learning for time series classification: a review (Ismail Fawaz 2019)
  • #CODE https://github.com/hfawaz/dl-4-tsc
  • https://medium.com/@hassanismailfawaz/deep-learning-for-time-series-classification-a-brief-overview-73b58767ed0f
• #PAPER TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classification (Shifaz 2020)

• Continuous wavelet transform

• Fourier analysis
  • Fast Fourier transform
    • A fast Fourier transform (FFT) is an algorithm that computes the discrete Fourier transform (DFT) of a sequence, or its inverse (IDFT).
  • Fourier Transform for Time Series
  • Understanding FFTs and Windowing

See AI/Causality/Causality

See AI/XAI