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 subsequencesForecasting | Classsification | Anomaly Detection | Segmentation | TSFeature | |
---|---|---|---|---|---|
Prophet | ✅ | ||||
Kats | ✅ | ✅ | ✅ | ||
GluonTS | ✅ | ✅ | ✅ | ||
NeuralProphet | ✅ | ✅ | ✅ | ||
arch | ✅ | ||||
AtsPy | ✅ | ||||
banpei | ✅ | ||||
cesium | ✅ | ||||
darts | ✅ | ||||
PaddleTS | ✅ | ✅ |
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 | ✅ |