Frequentist nonparametric goodness-of-fit tests via marginal likelihood ratios
DOI10.1016/j.csda.2015.10.013zbMath1468.62073OpenAlexW2196320994MaRDI QIDQ1659470
Taeryon Choi, Jeffrey D. Hart, Seongbaek Yi
Publication date: 15 August 2018
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2015.10.013
goodness-of-fit testskernel density estimationempirical null distributionmarginal likelihoodsbandwidth parameter
Computational methods for problems pertaining to statistics (62-08) Density estimation (62G07) Nonparametric hypothesis testing (62G10) Applications of statistics to physics (62P35) Statistical astronomy (85A35)
Uses Software
Cites Work
- Frequentist-Bayes lack-of-fit tests based on Laplace approximations
- A Bayesian approach to bandwidth selection for multivariate kernel density estimation
- Empirical likelihood ratios applied to goodness-of-fit tests based on sample entropy
- Comparing distributions
- An asymptotically efficient solution to the bandwidth problem of kernel density estimation
- On Kullback-Leibler loss and density estimation
- Exact mean integrated squared error
- Nonparametric curve estimation. Methods, theory, and applications
- Nonparametric smoothing and lack-of-fit tests
- Consistent cross-validated density estimation
- Nonparametric goodness-of-fit testing under Gaussian models
- Bayesian-motivated tests of function fit and their asymptotic frequentist properties
- A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation
- Saddle-point Methods for the Multinomial Distribution
- Smooth Tests of Goodness of Fit
- Goodness of Fit via Non-parametric Likelihood Ratios
- Bayes Factors
- An analysis of variance test for normality (complete samples)
- A Test of Goodness of Fit
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: Frequentist nonparametric goodness-of-fit tests via marginal likelihood ratios
