A note on non-parametric testing for Gaussian innovations in AR-ARCH models-Reference-Cited by-同舟云学术

A note on non-parametric testing for Gaussian innovations in AR-ARCH models

Published:2013-03-12 Issue:3 Volume:34 Page:362-367
ISSN:0143-9782
Container-title:Journal of Time Series Analysis
language:en
Short-container-title:J. Time Ser. Anal.

Author:

Neumeyer Natalie¹,Selk Leonie¹

Affiliation:

1. University of Hamburg; Department of Mathematics; Bundesstrasse 55 20146 Hamburg Germany

Publisher

Wiley

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/jtsa.12018/fullpdf

Reference22 articles.

1. Nonparametric estimation of the residual distribution;Akritas;Scandinavian Journal of Statistics,2001

2. Developing nonparametric conditional heteroscedastic autoregressive nonlinear model by using maximum likelihood method;Araveeporn;Chiang Mai Journal of Science,2011

3. Goodness-of-fit tests for multiplicative models with dependent data;Dette;Scandinavian Journal of Statistics,2009

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4. Oracally efficient estimation of autoregressive error distribution with simultaneous confidence band;The Annals of Statistics;2014-04-01

5. Testing for a Change of the Innovation Distribution in Nonparametric Autoregression: The Sequential Empirical Process Approach;Scandinavian Journal of Statistics;2013-09-13