Results 11 to 20 of about 159 (149)

Edgeworth expansions for GEL estimators

Journal of Multivariate Analysis, 2012
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Gubhinder Kundhi, Paul Rilstone
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Edgeworth and Cornish Fisher expansions and confidence intervals for the distribution, density and

Statistica, 2013
We show that kernel density estimates of bandwidth h=h(n)→0 satisfy the Cornish-Fisher assumption with parameter m=nh. This allows Cornish-Fisher expansions about the normal for standardized and Studentized kernel density estimates.
Christopher S. Withers, Saralees Nadarajah   +1 more
doaj   +1 more source

An Analytic Approach to Probabilistic Load Flow Incorporating Correlation Between Non-Gaussian Random Variables

Elektronika ir Elektrotechnika, 2018
This paper presents a cumulant-based method for probabilistic load flow (PLF) analysis which incorporates correlation between input random variables. Our approach can approximate non-Gaussian variables of all kinds (e.g.
Yu Huang, Qingshan Xu, Xianqiang Jiang, Yang Yang, Guang Lin   +4 more
doaj   +1 more source

Edgeworth Coefficients for Standard Multivariate Estimates

Axioms
I give for the first time explicit formulas for the coefficients needed for the fourth-order Edgeworth expansions of a multivariate standard estimate. I call these the Edgeworth coefficients.
Christopher Stroude Withers
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Inverting an Edgeworth Expansion

The 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.
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5th-Order Multivariate Edgeworth Expansions for Parametric Estimates

Mathematics
The only cases where exact distributions of estimates are known is for samples from exponential families, and then only for special functions of the parameters. So statistical inference was traditionally based on the asymptotic normality of estimates. To
C. S. Withers
doaj   +1 more source

An Edgeworth Expansion for $U$-Statistics

The Annals of Statistics, 1980
It is shown that, under some regularity conditions on the kernel, a one-sample $U$-statistic with kernel of degree two admits an asymptotic expansion with remainder term $o(N^{-1})$.
Callaert, H., Janssen, P., Veraverbeke, N.   +2 more
openaire   +3 more sources

Detecting Informed Trading Risk from Undercutting Activity

The Journal of Finance, EarlyView.
ABSTRACT We introduce a simple measure of informed trading risk, QIDres$QID^{res}$, the residual to liquidity quote‐improvement‐to‐deterioration ratio times −1$-1$. When facing with increased informed trading risk, liquidity providers compete less to provide liquidity, reducing their undercutting activity. Reductions in undercutting leave footprints in
YASHAR H. BARARDEHI, PETER DIXON, QIYU LIU   +2 more
wiley   +1 more source

The Distribution and Quantiles of the Sample Mean from a Stationary Process

Axioms
Edgeworth–Cornish–Fisher expansions are hugely important, as they give the distribution, density and quantiles of any standard estimate. Here we show that the sample mean of a univariate or multivariate stationary process is a standard estimate, so that ...
Christopher S. Withers
doaj   +1 more source

On the Foundational Arguments of Sufficient Dimension Reduction

WIREs Computational Statistics, Volume 18, Issue 2, June 2026.
Contemporary Sufficient Dimension Reduction, a versatile method for extracting material information from data, can serve as a preprocessor for classical modeling and inference, or as a standalone theory that leads directly to statistical inference. ABSTRACT Sufficient dimension reduction (SDR) refers to supervised methods of dimension reduction that ...
R. Dennis Cook
wiley   +1 more source