Kernel-based Hidden Markov Conditional Densities

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2022 Netherlands English Publisher:Elsevier BVJournal:SSRN Electronic Journal (eissn: 1556-5068,

Copyright policy )

Authors: Jan G. De Gooijer; Gustav Eje Henter; Ao Yuan;

doi: 10.2139/ssrn.4007364 , 10.1016/j.csda.2022.107431

handle: 11245.1/5bb0f3c3-3e53-44ba-bca8-d863eaf3e093

Kernel-based Hidden Markov Conditional Densities

- Summary
- Subjects
- Metrics

Abstract

zbMATH Open Web Interface contents unavailable due to conflicting licenses.

Country

Netherlands

Related Organizations

Keywords

330, Markov processes: estimation; hidden Markov models, nonlinearity, 510, Density estimation, Time series, auto-correlation, regression, etc. in statistics (GARCH), density estimation, nonparametric, time series, Applications of statistics to economics, hidden Markov model

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	2
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average