Extremes of two-step regression quantiles
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24510%2F10%3A%230000068" target="_blank" >RIV/46747885:24510/10:#0000068 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
Extremes of two-step regression quantiles
Original language description
The article deals with estimators of extreme value index based on two-step regression quantiles in the linear regression model. Two-step regression quantiles can be seen as a possible generalization of the quantile idea and as an alternative to regression quantiles. We derive the approximation of the tail quantile function of errors. Following Drees (1998) we consider a class of smooth functionals of the tail quantile function as a tool for the construction of estimators in the linear regression context. Pickands, maximum likelihood and probability weighted moments estimators are illustrated on simulated data.
Czech name
—
Czech description
—
Classification
Type
C - Chapter in a specialist book
CEP classification
BA - General mathematics
OECD FORD branch
—
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
Nonparametrics and Robustness in Modern Statistical Inference and Time Series Analysis
ISBN
978-0-940600-80-5
Number of pages of the result
11
Pages from-to
—
Number of pages of the book
268
Publisher name
Institute of Mathematical Statistics
Place of publication
Beachwood, Ohio, USA
UT code for WoS chapter
—