On entropy-based goodness-of-fit test for asymmetric Student-t and exponential power distributions

DOI10.1080/00949655.2016.1196690zbMath1492.62049OpenAlexW2428350866WikidataQ115551904 ScholiaQ115551904MaRDI QIDQ5106768

Minjo Kim, Sangyeol Lee

Publication date: 22 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2016.1196690

zbMATH Keywords

bootstrap methodgoodness-of-fit testasymmetric exponential power distributionentropy testasymmetric Student-\(t\) distribution

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Parametric hypothesis testing (62F03) Asymptotic properties of parametric tests (62F05)

Related Items (3)

On entropy goodness-of-fit test based on integrated distribution function ⋮ Bootstrap entropy test for general location-scale time series models with heteroscedasticity ⋮ Statistical inference for a general class of distributions with time-varying parameters

Uses Software

• CAViaR

Cites Work

• Properties and estimation of asymmetric exponential power distribution
• A generalized asymmetric Student-\(t\) distribution with application to financial econometrics
• A maximum entropy type test of fit
• Nonlinear expectile regression with application to value-at-risk and expected shortfall estimation
• Maximum entropy test for GARCH models
• A maximum entropy type test of fit: composite hypothesis case
• Autoregressive Conditional Density Estimation
• Value-at-risk forecasting based on Gaussian mixture ARMA–GARCH model
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