Improved Approach for the Maximum Entropy Deconvolution Problem [PDF]
Entropy, 2021 The probability density function (pdf) valid for the Gaussian case is often applied for describing the convolutional noise pdf in the blind adaptive deconvolution problem, although it is known that it can be applied only at the latter stages of the ...
Shay Shlisel, Monika Pinchas
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Omnibus test for normality based on the Edgeworth expansion. [PDF]
PLoS ONE, 2020 Statistical inference in the form of hypothesis tests and confidence intervals often assumes that the underlying distribution is normal. Similarly, many signal processing techniques rely on the assumption that a stationary time series is normal.
Agnieszka Wyłomańska +2 more
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Rearranging Edgeworth-Cornish-Fisher expansions [PDF]
Economic Theory, 2009 17 pages, 3 ...
Chernozhukov, Victor +2 more
core +8 more sources
A Novel Technique for Achieving the Approximated ISI at the Receiver for a 16QAM Signal Sent via a FIR Channel Based Only on the Received Information and Statistical Techniques [PDF]
Entropy, 2020 A single-input-multiple-output (SIMO) channel is obtained from the use of an array of antennas in the receiver where the same information is transmitted through different sub-channels, and all received sequences are distinctly distorted versions of the ...
Hadar Goldberg, Monika Pinchas
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Inverting an Edgeworth Expansion
Annals of Statistics, 1983 We provide a method for inverting a general Edgeworth expansion, so as to correct a statistic for the effects of non-normality. This technique is applied to the special case of the "Studentized" mean. Explicit formulae are given for the correction terms.
exaly +3 more sources
Edgeworth expansion by Stein’s method
Bernoulli, 2022 Edgeworth expansion provides higher-order corrections to the normal approximation for a probability distribution. The classical proof of Edgeworth expansion is via characteristic functions. As a powerful method for distributional approximations, Stein's method has also been used to prove Edgeworth expansion results.
Fang, Xiao, Liu, Song-Hao
openaire +3 more sources
Improving Convergence of Binomial Schemes and the Edgeworth Expansion
Risks, 2016 Binomial trees are very popular in both theory and applications of option pricing. As they often suffer from an irregular convergence behavior, improving this is an important task. We build upon a new version of the Edgeworth expansion for lattice models
Alona Bock, Ralf Korn
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Signatures of the Anthropocene: Population Genomic Structure Detected in Pennsylvania Coyotes. [PDF]
Ecol EvolCoyotes rapidly expanded across eastern North America and are highly dispersive ecological generalists, leading prior studies to report little spatial genetic structure. Using genome‐wide data from 1199 coyotes sampled over a decade in the northeastern United States, we detected subtle but significant population structure, with two weakly clinal ...
Marshall CA +15 more
europepmc +2 more sources
La contribución de Edgeworth al éxito del macadam. Expansión internacional en sus albores
Informes de la Construccion, 2021 En la historia de la ingeniería de carreteras, el nombre de John Loudon McAdam tiene un lugar de honor como el inventor del firme de macadam. Sin embargo, el diseño original de McAdam presentaba algunas limitaciones que fueron resueltas por Richard ...
José Manuel Sanz García +2 more
doaj +1 more source
Edgeworth Expansion of the Parametric Bootstrap t-statistic for Linear Regression Processes with Strongly Dependent Errors [PDF]
Journal of Statistical Theory and Applications (JSTA), 2015 The purpose of this paper is to provide a valid Edgeworth expansion for the parametric bootstrap t-statistic of a linear regression process whose error terms are stationary, Gaussian, and strongly dependent time series.
Mosisa Aga
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