Time series is a series of data points indexed in time order.
时间序列分析具体包括的任务:
检索Indexing (query by content): given a time series and some similarity measure, find the nearest matching time series.
聚类Clustering: find groups (clusters) of similar time series.
分类Classification: assign a time series to a predefined class.
分割Segmentation (Summarization): create an accurate approximation of a time series by reducing its dimensionality while retaining its essential features.
预测Forecasting (Prediction): given a time series dataset up to a given time tn, forecast the next values.
异常检测Anomaly Detection: find abnormal data points or subsequences.
因果分析Rules Discovery: find the rules that may govern associations between sets of time series or subsequences
Intel 时间序列分析:讲授时间序列分析,以及用于预测、处理和识别顺序数据的方法。
时间序列和平稳数据简介
数据平滑化、自相关性和自回归积分滑动平均 (ARIMA) 模型等应用
高级时间序列概念,如卡尔曼滤波器 (Kalman Filter) 和傅里叶变换 (Fourier Transformation)
用于时间序列分析的深度学习架构和方法

Kats,推荐指数:⭐⭐
主页:https://facebookresearch.github.io/Kats/
Github:https://github.com/facebookresearch/Kats
darts,推荐指数:⭐⭐
介绍:a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks.
主页:https://unit8co.github.io/darts/
Github:https://github.com/unit8co/darts
GluonTS,推荐指数:⭐⭐⭐⭐
主页:https://ts.gluon.ai/index.html
Github:https://github.com/awslabs/gluon-ts/
NeuralProphet,推荐指数:⭐⭐⭐⭐
主页:https://neuralprophet.com/
Github:https://github.com/ourownstory/neural_prophet
arch
介绍:Autoregressive Conditional Heteroskedasticity (ARCH) and other tools for financial econometrics, written in Python.
主页:https://arch.readthedocs.io/en/latest/
Github:https://github.com/bashtage/arch
AtsPy
介绍:Automated Time Series Models in Python
Github:https://github.com/firmai/atspy
banpei
介绍:Anomaly detection library based on singular spectrum transformation
Github:https://github.com/tsurubee/banpei
cesium
介绍:end-to-end machine learning platform for time-series, from calculation of features to model-building to predictions.
主页:https://cesium-ml.org/
Github:https://github.com/cesium-ml/cesium
pyfbad
Github:https://github.com/Teknasyon-Teknoloji/pyfbad
更多的模型介绍可以查阅论文[arxiv 2021]A systematic review of Python packages for time series analysis.
| Model | Univariate | Multivariate | Probabilistic | Multiple-series training |
|---|---|---|---|---|
ARIMA | ✅ | |||
| ✅ | ||||
VARIMA | ✅ | ✅ | ||
AutoARIMA | ✅ | |||
ExponentialSmoothing | ✅ | |||
| ✅ | ||||
Theta and FourTheta | ✅ | |||
Prophet | ✅ | |||
| ✅ | ||||
FFT (Fast Fourier Transform) | ✅ | |||
RegressionModel (incl RandomForest, LinearRegressionModel and LightGBMModel) | ✅ | ✅ | ||
| ✅ | ||||
RNNModel (incl. LSTM and GRU); equivalent to DeepAR in its probabilistic version | ✅ | ✅ | ✅ | ✅ |
BlockRNNModel (incl. LSTM and GRU) | ✅ | ✅ | ✅ | ✅ |
NBEATSModel | ✅ | ✅ | ✅ | ✅ |
TCNModel | ✅ | ✅ | ✅ | ✅ |
TransformerModel | ✅ | ✅ | ✅ | ✅ |
TFTModel (Temporal Fusion Transformer) | ✅ | ✅ | ✅ | ✅ |
| Naive Baselines | ✅ | |||
[IJCAI 2021] Time Series Data Augmentation for Deep Learning: A Survey
[arxiv 2020] An empirical survey of data augmentation for time series classification with neural networks
UCR Time Series Classification Archive
UEA & UCR Time Series Classification Repository