Metadata-Version: 1.1
Name: iAROnline
Version: 0.0.1
Summary: Online estimation methods for the irregularly observed autoregressive (iAR) model
Home-page: https://github.com/felipeelorrieta/Onlineiar
Author: Felipe Elorrieta
Author-email: <felipe.elorrieta@usach.cl>
License: MIT
Description: Data sets, functions and scripts with examples to implement online estimation methods for the irregularly observed autoregressive (iAR) model (Eyheramendy et al.(2018) <doi:10.1093/mnras/sty2487>). The online learning algorithms implemented are: gradient descent (IAR_OGD), Newton-step (IAR-ONS) and Kalman filter recursions (IAR-OBR).
Keywords: irregulary observed time series,autoregressive,online estimation methods
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Operating System :: Microsoft :: Windows :: Windows 11
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
