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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Empirical likelihood inference in autoregressive models with time-varying variances
Statistical Theory and Related Fields, 2022 This paper develops the empirical likelihood ( $ \mathrm {EL} $ ) inference procedure for parameters in autoregressive models with the error variances scaled by an unknown nonparametric time-varying function.
Yu Han, Chunming Zhang
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Empirical Likelihood Confidence Region for Parameters in Semi-linear Errors-in-Variables Models [PDF]
, 2006 This paper proposes a constrained empirical likelihood confidence region for a parameter in the semi-linear errors-in-variables model. The confidence region is constructed by combining the score function corresponding to the squared orthogonal distance
Kong, Efang, Cui, Hengjian
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Influence Function-Based Empirical Likelihood And Generalized Confidence Intervals For Lorenz Curve
, 2020 This thesis aims to solve confidence interval estimation problems for Lorenz curve. First, we propose new nonparametric confidence intervals with influence function-based empirical likelihood method.
Shi, Yuyin
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Sample Empirical Likelihood under Complex Survey Design and Bayesian Jackknife Empirical Likelihood-based Inference for Missing Data and Partial AUC [PDF]
The empirical likelihood (EL), introduced by Owen (1988, 1990), is a powerful tool for constructing confidence intervals in nonparametric settings. Significant developments based on empirical likelihood have been made in recent years.
Wang, Yuke
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Weighted Graph-Based Two-Sample Test via Empirical Likelihood
MathematicsIn network data analysis, one of the important problems is determining if two collections of networks are drawn from the same distribution. This problem can be modeled in the framework of two-sample hypothesis testing.
Xiaofeng Zhao, Mingao Yuan
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melt: Multiple Empirical Likelihood Tests in R
Journal of Statistical SoftwareEmpirical likelihood enables a nonparametric, likelihood-driven style of inference without relying on assumptions frequently made in parametric models.
Eunseop Kim +2 more
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Testing for Serial Correlation in Autoregressive Exogenous Models with Possible GARCH Errors
Entropy, 2022 Autoregressive exogenous, hereafter ARX, models are widely adopted in time series-related domains as they can be regarded as the combination of an autoregressive process and a predictive regression.
Hanqing Li +3 more
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Degradation mechanism of the von Willebrand factor A2 domain by nattokinase
FEBS Letters, EarlyView.Nattokinase, a natto‐derived protease, exhibits potent antithrombotic effects. This study demonstrates that nattokinase directly cleaves the von Willebrand factor (vWF) A2 domain in vitro. Unlike the native regulator ADAMTS13, nattokinase degrades folded vWF independently of shear stress.
Ryuichi Hyakumoto +3 more
wiley +1 more source