Results 21 to 30 of about 1,058,580 (309)
Leida xuebao, 2014 The X-Estimator (XE) for the K-distribution shape parameter v based on the zlog(z) expectation can be computed without solving nonlinear equations; thus, it has high estimating efficiency.
Li Da-peng
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Improved Average Estimation in Seemingly Unrelated Regressions
Econometrics, 2020 In this paper, we propose an efficient weighted average estimator in Seemingly Unrelated Regressions. This average estimator shrinks a generalized least squares (GLS) estimator towards a restricted GLS estimator, where the restrictions represent possible
Ali Mehrabani, Aman Ullah
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Moment Estimation and Dithered Quantization [PDF]
IEEE Signal Processing Letters, 2006 This letter examines the influence of low-bit quantization on moment estimators with special emphasis on the 1-bit case. Moment estimators are especially useful if no prior knowledge on the distribution of the observations is available or if an ML approach is analytically intractable or computationally infeasible.
Stefan Geirhofer +2 more
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Application of the Heavy-tailed Estimation in Financial Data
Journal of Harbin University of Science and Technology, 2019 There exist many marginal distributions of high frequency time series data in the Heavy-tailed distribution which stores a great deal of information in its tail.
CHEN Hai-long, HUANG Fei, XIE Sheng
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Moment estimates for Lévy Processes
Electronic Communications in Probability, 2008 For real Lévy processes $(X\_t)\_{t \geq 0}$ having no Brownian component with Blumenthal-Getoor index $β$, the estimate $\E \sup\_{s \leq t} | X\_s - a\_p s |^p \leq C\_p t$ for every $t \in [0,1]$ and suitable $a\_p \in \R$ has been established by Millar \cite{MILL} for $β< p \leq 2$ provided $X\_1 \in L^p$. We derive extensions of these estimates
Luschgy, Harald, Pagès, Gilles
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Moment Multicalibration for Uncertainty Estimation
CoRR, 2020 We show how to achieve the notion of "multicalibration" from Hébert-Johnson et al. [2018] not just for means, but also for variances and other higher moments. Informally, it means that we can find regression functions which, given a data point, can make point predictions not just for the expectation of its label, but for higher moments of its label ...
Christopher Jung 0001 +4 more
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Determining the Unbiased Estimator of the Population Geometric Measures of Variation about the Mean [PDF]
, 2021 Geometric Measures of Variation about the mean is a measure that uses the geometric averaging technique to average the deviations from the mean. From previous studies, it has been determined that the measure is more precise in estimating the average ...
Troon, Benedict, Benedict Troon
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A note on the bootstrap method for testing the existence of finite moments
Statistica, 2014 This paper discusses a bootstrap-based test, which checks if finite moments exist, and indicates cases of possible misapplication. It notes, that a procedure for finding the smallest power to which observations need to be raised, such that the test ...
Igor Fedotenkov
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The Statistical Curvature of Seemingly Unrelated Unrestricted Regression Equations. [PDF]
The Egyptian Statistical Journal, 1997 We study the finite sample properties of an asymptotically efficient estimator for coefficients of seemingly unrelated unrestricted regression (SUUR) equations. Zellner (1963) derived the exact probability density function of the SUUR estimator.
Ahmed Youssef
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Measuring the Sensitivity of Parameter Estimates to Estimation Moments* [PDF]
The Quarterly Journal of Economics, 2017 AbstractWe propose a local measure of the relationship between parameter estimates and the moments of the data they depend on. Our measure can be computed at negligible cost even for complex structural models. We argue that reporting this measure can increase the transparency of structural estimates, making it easier for readers to predict the way ...
Gentzkow, Matthew +2 more
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