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DSGE Estimation Using Generalized Empirical Likelihood and Generalized Minimum Contrast [PDF]
EntropyWe investigate the performance of estimators of the generalized empirical likelihood and minimum contrast families in the estimation of dynamic stochastic general equilibrium models, with particular attention to the robustness properties under ...
Gilberto Boaretto +1 more
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Semiparametric fractional imputation using empirical likelihood in survey sampling [PDF]
Statistical Theory and Related Fields, 2017 The empirical likelihood method is a powerful tool for incorporating moment conditions in statistical inference. We propose a novel application of the empirical likelihood for handling item non-response in survey sampling.
Sixia Chen, Jae kwang Kim
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Confidence Regions for Parameters in Stationary Time Series Models With Gaussian Noise
Frontiers in Physics, 2022 This article develops two new empirical likelihood methods for long-memory time series models based on adjusted empirical likelihood and mean empirical likelihood.
Xiuzhen Zhang +3 more
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Mean Empirical Likelihood [PDF]
Computational Statistics & Data Analysis, 2019 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wei Liang 0003 +2 more
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Mathematics, 2023 This paper studies the estimation and inference of a partially linear varying coefficient spatial autoregressive panel data model with fixed effects. By means of the basis function approximations and the instrumental variable methods, we propose a two ...
Sanying Feng, Tiejun Tong, Sung Nok Chiu
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On copula moment: empirical likelihood based estimation method [PDF]
Arab Journal of Mathematical Sciences, 2022 Purpose – In this paper, the authors applied the empirical likelihood method, which was originally proposed by Owen, to the copula moment based estimation methods to take advantage of its properties, effectiveness, flexibility and reliability of the ...
Jihane Abdelli, Brahim Brahimi
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A Unified Test for the AR Error Structure of an Autoregressive Model
Axioms, 2022 A direct application of autoregressive (AR) models with independent and identically distributed (iid) errors is sometimes inadequate to fit the time series data well.
Xinyi Wei +4 more
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Split sample empirical likelihood
Computational Statistics & Data Analysis, 2020 We propose a new approach that combines multiple non-parametric likelihood-type components to build a data-driven approximation of the true likelihood function. Our approach is built on empirical likelihood, a non-parametric approximation of the likelihood function.
Adam Jaeger, Nicole A. Lazar
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Estimation of quantile regression model without longitudinal data and with auxiliary information
Xi'an Gongcheng Daxue xuebao, 2021 In order to study the estimation of the quantile regression model with missing longitudinal data and auxiliary information, the parameter estimation and asymptotic normality of linear quantile regression model are given by using inverse probability ...
Yuting ZHANG +2 more
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A Blockwise Empirical Likelihood Test for Gaussianity in Stationary Autoregressive Processes
Mathematics, 2023 A new and simple blockwise empirical likelihood moment-based procedure to test if a stationary autoregressive process is Gaussian has been proposed. The proposed test utilizes the skewness and kurtosis moment constraints to develop the test statistic ...
Chioneso S. Marange +3 more
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