Results 21 to 30 of about 257,916 (299)
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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A selective review of statistical methods using calibration information from similar studies
Statistical Theory and Related Fields, 2022 In the era of big data, divide-and-conquer, parallel, and distributed inference methods have become increasingly popular. How to effectively use the calibration information from each machine in parallel computation has become a challenging task for ...
Jing Qin, Yukun Liu, Pengfei Li
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Bayesian computation via empirical likelihood. [PDF]
Proc Natl Acad Sci U S A, 2013 Approximate Bayesian computation has become an essential tool for the analysis of complex stochastic models when the likelihood function is numerically unavailable. However, the well-established statistical method of empirical likelihood provides another
Mengersen KL, Pudlo P, Robert CP.
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A Robust Version of the Empirical Likelihood Estimator
Mathematics, 2021 In this paper, we introduce a robust version of the empirical likelihood estimator for semiparametric moment condition models. This estimator is obtained by minimizing the modified Kullback–Leibler divergence, in its dual form, using truncated ...
Amor Keziou, Aida Toma
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, 2022 The empirical likelihood method is a reliable data analysis tool in all statistical areas for its nonparametric features with parametric likelihood benefits. Because of the versatility of this method, we investigate its performance under survival and non-
Satter, Faysal I
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Functional generalized empirical likelihood estimation for conditional moment restrictions [PDF]
, 2022 Important problems in causal inference, economics, and, more generally, robust machine learning can be expressed as conditional moment restrictions, but estimation becomes challenging as it requires solving a continuum of unconditional moment ...
Muandet, Krikamol +3 more
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Testing the Intercept of a Balanced Predictive Regression Model
Entropy, 2022 Testing predictability is known to be an important issue for the balanced predictive regression model. Some unified testing statistics of desirable properties have been proposed, though their validity depends on a predefined assumption regarding whether ...
Qijun Wang +3 more
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Empirical Phi-discrepancies and quasi-empirical likelihood: exponential bounds
ESAIM: Proceedings and Surveys, 2015 We review some recent extensions of the so-called generalized empirical likelihood method, when the Kullback distance is replaced by some general convex divergence.
Bertail Patrice +2 more
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