Adjusted empirical likelihood with high-order precision
Empirical likelihood is a popular nonparametric or semi-parametric statistical method with
many nice statistical properties. Yet when the sample size is small, or the dimension of the …
many nice statistical properties. Yet when the sample size is small, or the dimension of the …
Finite-sample properties of the adjusted empirical likelihood
J Chen, Y Huang - Journal of Nonparametric Statistics, 2013 - Taylor & Francis
Empirical likelihood-based confidence intervals for the population mean have many
interesting properties [Owen, AB (1988),'Empirical Likelihood Ratio Confidence Intervals for …
interesting properties [Owen, AB (1988),'Empirical Likelihood Ratio Confidence Intervals for …
Adjusted empirical likelihood and its properties
J Chen, AM Variyath, B Abraham - Journal of Computational and …, 2008 - Taylor & Francis
Computing a profile empirical likelihood function, which involves constrained maximization,
is a key step in applications of empirical likelihood. However, in some situations, the …
is a key step in applications of empirical likelihood. However, in some situations, the …
Weighted empirical likelihood inference
C Wu - Statistics & probability letters, 2004 - Elsevier
A weighted empirical likelihood approach is proposed to take account of the heteroscedastic
structure of the data. The resulting weighted empirical likelihood ratio statistic is shown to …
structure of the data. The resulting weighted empirical likelihood ratio statistic is shown to …
Empirical likelihood on the full parameter space
M Tsao, F Wu - 2013 - projecteuclid.org
We extend the empirical likelihood of Owen [Ann. Statist. 18 (1990) 90–120] by partitioning
its domain into the collection of its contours and mapping the contours through a continuous …
its domain into the collection of its contours and mapping the contours through a continuous …
Weighted empirical likelihood estimates and their robustness properties
Maximum likelihood methods are by far the most popular methods for deriving statistical
estimators. However, parametric likelihoods require distributional specifications. The …
estimators. However, parametric likelihoods require distributional specifications. The …
Large dimensional empirical likelihood
The empirical likelihood is a versatile nonparametric approach to testing hypotheses and
constructing confidence regions. However it is not clear if Wilks' Theorem still works in high …
constructing confidence regions. However it is not clear if Wilks' Theorem still works in high …
A review of recent advances in empirical likelihood
Empirical likelihood is widely used in many statistical problems. In this article, we provide a
review of the empirical likelihood method, due to its significant development in recent years …
review of the empirical likelihood method, due to its significant development in recent years …
Mean empirical likelihood
Empirical likelihood methods are widely used in different settings to construct the confidence
regions for parameters which satisfy the moment constraints. However, the empirical …
regions for parameters which satisfy the moment constraints. However, the empirical …
Approximate jackknife empirical likelihood method for estimating equations
L Peng - Canadian Journal of Statistics, 2012 - Wiley Online Library
It is known that the profile empirical likelihood method based on estimating equations is
computationally intensive when the number of nuisance parameters is large. Recently, Li …
computationally intensive when the number of nuisance parameters is large. Recently, Li …