Neyman smooth goodness-of-fit tests for the marginal distribution of dependent data

DOI10.1007/s10463-009-0260-2zbMath1441.62224OpenAlexW2096626632MaRDI QIDQ645527

Janis Valeinis, Jean-Pierre Stockis, Axel Munk, Götz Giese

Publication date: 8 November 2011

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: http://resolver.sub.uni-goettingen.de/purl?gs-1/8651

zbMATH Keywords

goodness-of-fitimplied volatilityNeyman's smooth teststrongly mixing process

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Non-Markovian processes: hypothesis testing (62M07)

Related Items (5)

Comparing two mixing densities in nonparametric mixture models ⋮ Characteristic function-based hypothesis tests under weak dependence ⋮ Comparing the marginal densities of two strictly stationary linear processes ⋮ Semiparametric density testing in the contamination model ⋮ Data driven smooth test of comparison for dependent sequences

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