Semiparametric methods in nonlinear time series analysis: a selective review

Patrick Saart, Jiti Gao, Nam-Hyun Kim

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

Abstract

Tune series analysis is a tremendous research area in statistics and econometrics. In a previous review, the author was able to break down up 15 key areas of research interest in time series analysis. Nonetheless, the aim of the review in this current paper is not to cover a wide range of somewhat unrelated topics on the subject, but the key strategy of the review in this paper is to begin with a core the curse of dimensionality in nonparametric time series analysis, and explore further in a metaphorical domino-effect fashion into other closely related areas in semiparametric methods in nonlinear time series analysis.
Original languageEnglish
Pages (from-to)141 - 169
Number of pages29
JournalJournal of Nonparametric Statistics
Volume26
Issue number1
DOIs
Publication statusPublished - 2014

Cite this