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 …
Jackknife empirical likelihood inference for the mean absolute deviation
In statistics mean absolute deviation plays an important role in measuring spread of a data.
In this paper, we focus on using the jackknife, the adjusted and the extended jackknife …
In this paper, we focus on using the jackknife, the adjusted and the extended jackknife …
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 …
Transforming the empirical likelihood towards better accuracy
Under‐coverage has been a long‐standing issue with the empirical likelihood confidence
region. Several methods can be used to address this issue, but they all add complexity to the …
region. Several methods can be used to address this issue, but they all add complexity to the …
Empirical likelihood for outlier detection and estimation in autoregressive time series
R Baragona, F Battaglia… - Journal of Time Series …, 2016 - Wiley Online Library
Identification and estimation of outliers in time series is proposed by using empirical
likelihood methods. Theory and applications are developed for stationary autoregressive …
likelihood methods. Theory and applications are developed for stationary autoregressive …
Modified empirical likelihood-based confidence intervals for data containing many zero observations
P Stewart, W Ning - Computational Statistics, 2020 - Springer
Data containing many zeroes is popular in statistical applications, such as survey data. A
confidence interval based on the traditional normal approximation may lead to poor …
confidence interval based on the traditional normal approximation may lead to poor …
Extended empirical likelihood for estimating equations
M Tsao, F Wu - Biometrika, 2014 - academic.oup.com
We derive an extended empirical likelihood for parameters defined by estimating equations
which generalizes the original empirical likelihood to the full parameter space. Under mild …
which generalizes the original empirical likelihood to the full parameter space. Under mild …
Jackknife empirical likelihood for the error variance in linear models
Variance estimation is a fundamental yet important problem in statistical modelling. In this
paper, we propose jackknife empirical likelihood (JEL) methods for the error variance in a …
paper, we propose jackknife empirical likelihood (JEL) methods for the error variance in a …
Nonparametric confidence intervals for generalized Lorenz curve using modified empirical likelihood
S Ratnasingam, S Wallace, I Amani, J Romero - Computational Statistics, 2024 - Springer
The Lorenz curve portrays income distribution inequality. In this article, we develop three
modified empirical likelihood (EL) approaches, including adjusted empirical likelihood …
modified empirical likelihood (EL) approaches, including adjusted empirical likelihood …
Confidence intervals of mean residual life function in length-biased sampling based on modified empirical likelihood
S Ratnasingam, W Ning - Journal of Biopharmaceutical Statistics, 2023 - Taylor & Francis
The mean residual life (MRL) function is one of the basic parameters of interest in survival
analysis. In this paper, we develop three procedures based on modified versions of …
analysis. In this paper, we develop three procedures based on modified versions of …