# featurize_time_series的输入格式: # - time_series: list of TimeSeries objects or list of (t, m, e) tuples/lists # - features_to_use: list of feature names # 创建一个Cesium TimeSeries对象 (可选,但更规范) from cesium.time_s
The library seems to be promising and it has just released its first version. Some tutorials can be foundhere. Github:https://github.com/facebookresearch/Kats 7. sktime: Sktime library as the name suggests is a unified python library that works for time series data and is scikit-learn comp...
TSFEL (Time Series Feature Extraction Library)是一个用于时间序列数据的特征提取的Python包。它允许用户在不需要大量编程工作的情况下，对时间序列进行探索性的特征提取。TSFEL能自动提取超过60种不同的统计、时域和频域特征。它的主要功能包括直观快速的部署、计算复杂度评估、详细的文档说明，以及易于扩展新特征的能力...
PyFlux is an open source time series library for Python. The library has a good array of modern time series models, as well as a flexible array of inference options (frequentist and Bayesian) that can be applied to these models. By combining breadth of models with breadth of inference, PyFl...
PyPond - Python Pond timeseries library. Overview PyPond is a Python implementation of the JavaScriptPond timeseries library. At a very high level, both implementations offer classes and structures to collect, manipulate and transmit timeseries data. Time series transmission is done via a JSON-bas...
TSFEL (Time Series Feature Extraction Library)是一个用于时间序列数据的特征提取的Python包。它允许用户在不需要大量编程工作的情况下,对时间序列进行探索性的特征提取。TSFEL能自动提取超过60种不同的统计、时域和频域特征。它的主要功能包括直观快速的部署、计算复杂度评估、详细的文档说明,以及易于扩展新特征的能力。
dartsis 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. The models can all be used in the same way, usingfit()andpredict()functions, similar to scikit-learn. The library also makes...
Exploring Time Library: Common Functions Let’s take a look at some of the most commonly used functions of the time library with some examples. 1. time() You can use thetime()function to return the current time in seconds. It measures the current time since the beginning of the epoch, ...
library(xts),library(timeSeires),library(zoo)—时间基础包 library(urca)--进行单位根检验 library(tseries)--arma模型 library(fUnitRoots)--进行单位根检验 library(FinTS)--调用其中的自回归检验函数 library(fGarch)--GARCH模型 library(nlme)--调用其中的gls函数 ...
df=pd.read_csv('AirPassengers.csv',delimiter=",")series=TimeSeries.from_dataframe(df,'Month','#Passengers')train,val=series[:-36],series[-36:]# 拟合指数平滑模型,并对验证系列的持续时间进行(概率)预测: model=ExponentialSmoothing()model.fit(train)prediction=model.predict(len(val),num_samples=...