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Adjusted empirical likelihood with high-order precision [PDF]
, 2010 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 accompanying estimating function is high, the application of the ...
Chen, Jiahua, Liu, Yukun
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Two-step semiparametric empirical likelihood inference [PDF]
The Annals of Statistics, 2020 In both parametric and certain nonparametric statistical models, the empirical likelihood ratio satis es a nonparametric version of Wilks' theorem. For many semiparametric models, however, the commonly used two-step (plug-in) empirical likelihood ratio is not asymptotically distribution-free, that is, its asymptotic distribution contains unknown ...
Van Keilegom, Ingrid +2 more
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Bounds on coverage probabilities of the empirical likelihood ratio confidence regions [PDF]
, 2004 This paper studies the least upper bounds on coverage probabilities of the empirical likelihood ratio confidence regions based on estimating equations.
Tsao, Min
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Improving Probability-Weighted Moment Methods for the Generalized Extreme Value Distribution
Revstat Statistical Journal, 2008 In 1985 Hosking et al. estimated with the so-called Probability-Weighted Moments (PWM) method the parameters of the Generalized Extreme Value (GEV) distribution, the latter being classically fitted to maxima of sequences of independent and identically ...
Jean Diebolt +3 more
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Empirical likelihood estimation of the spatial quantile regression [PDF]
, 2012 The spatial quantile regression model is a useful and flexible model for analysis of empirical problems with spatial dimension. This paper introduces an alternative estimator for this model.
A Owen +32 more
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Weighted empirical likelihood inference [PDF]
Statistics & Probability Letters, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Empirical Likelihood for Random Sets [PDF]
Journal of the American Statistical Association, 2017 In many statistical applications, the observed data take the form of sets rather than points. Examples include bracket data in survey analysis, tumor growth and rock grain images in morphology analysis, and noisy measurements on the support function of a convex set in medical imaging and robotic vision.
Adusumilli, Karun, Otsu, Taisuke
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Revised empirical likelihood [PDF]
, 2010 Empirical Likelihood (EL) and other methods that operate within the Empirical Estimating Equations (E3) approach to estimation and inference are challenged by the Empty Set Problem (ESP). ESP concerns the possibility that a model set, which is data-dependent, may be empty for some data sets.
Grendar, Marian +3 more
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Empirical likelihood based testing for regression [PDF]
, 2007 Consider a random vector $(X,Y)$ and let $m(x)=E(Y|X=x)$. We are interested in testing $H_0:m\in {\cal M}_{\Theta,{\cal G}}=\{\gamma(\cdot,\theta,g):\theta \in \Theta,g\in {\cal G}\}$ for some known function $\gamma$, some compact set $\Theta \subset $IR$
Manteiga, Wenceslao González +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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