iAROnline

Name	iAROnline JSON
Version	0.0.3 JSON
	download
home_page	https://github.com/felipeelorrieta/Onlineiar
Summary	Online estimation methods for the irregularly observed autoregressive (iAR) model
upload_time	2023-02-07 17:53:00
maintainer
docs_url	None
author	Felipe Elorrieta
requires_python
license	MIT
keywords	irregulary observed time series autoregressive online estimation methods
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            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).
            

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