Results 31 to 40 of about 161 (150)

Expansions for the Conditional Density and Distribution of a Standard Estimate

Stats
Conditioning is a very useful way of using correlated information to reduce the variability of an estimate. Conditioning an estimate on a correlated estimate, reduces its covariance, and so provides more precise inference than using an unconditioned ...
Christopher S. Withers
doaj   +1 more source

Bed Topography and Subglacial Conditions of Denman Glacier, East Antarctica: Insights From Magnetotelluric Data and Interdisciplinary Studies

Journal of Geophysical Research: Earth Surface, Volume 131, Issue 7, July 2026.
Abstract Understanding the basal conditions of East Antarctica's outlet glaciers is critical for accurately modeling future ice‐sheet evolution. Denman Glacier, one of the continent's fastest‐flowing glaciers, has been identified in bed‐topography models as occupying the deepest continental trough on Earth, potentially acting as a major outlet of the ...
Maria Constanza Manassero, Kate Selway, Tobias Stål, Matthias Scheiter, Mareen Loesing, Felicity McCormack, Jacqueline A. Halpin, Bernd Kulessa, Anya M. Reading   +8 more
wiley   +1 more source

An Analogue to the Edgeworth–Esseen Expansion

Journal of Mathematical Analysis and Applications, 1998
Let \(f\) be a bounded, measurable function on \([-\pi, \pi]\) and let \((a_{n\nu}: \nu=0,\pm 1,\pm 2,\dots)\) be the Fourier coefficients of the powers \(f^n\) for \(n= 1,2,\dots\)\ .
openaire   +2 more sources

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

On Edgeworth Expansions in Generalized Urn Models [PDF]

Journal of Theoretical Probability, 2012
The random vector of frequencies in a generalized urn model is viewed as conditionally independent random variables, given their sum. Such a representation is exploited to derive Edgeworth expansions for a sum of functions of such frequencies. Applying these results to urn models such as with- and without-replacement sampling schemes as well as the ...
Mirakhmedov, S. M., Jammalamadaka, S. Rao, Mohamed, Ibrahim B.   +2 more
openaire   +2 more sources

Little Known Facts, Controversies and Misconceptions About Cranial Motor Nuclei (and a New Classification for All Motoneurons, Cranial, and Spinal)

Journal of Comparative Neurology, Volume 534, Issue 4, April 2026.
ABSTRACT Cranial nerves represent a notoriously complex province of the neuroanatomical landscape of the vertebrates. Here, we offer a selection of the anatomic, genetic, and developmental features of their efferent component that are often misrepresented, ignored or controversial, as a complement to more exhaustive treatments of the subject.
Margaux Sivori, Bowen Dempsey, Jean‐François Brunet   +2 more
wiley   +1 more source

The Distribution and Quantiles of Sample Autocovariances and Autocorrelations of Sample Moments from a Stationary Process

Axioms
This paper gives expansions for the distribution, density and quantiles of any estimate that is a smooth function of the sample cross-moments of a stationary process.
Christopher Stroude Withers
doaj   +1 more source

Joint Estimation and Bandwidth Selection in Partially Parametric Models

Journal of Applied Econometrics, Volume 41, Issue 3, Page 227-239, April/May 2026.
ABSTRACT We propose a single‐step approach to estimating a model with both a known nonlinear parametric component and an unknown nonparametric component. We study the large sample behavior of a simultaneous optimization routine that estimates both the parameter vector of the parametric component and the bandwidth vector used to smooth the unknown ...
Daniel J. Henderson, Nadine McCloud, Christopher F. Parmeter   +2 more
wiley   +1 more source

New Methods for Multivariate Normal Moments

Stats
Multivariate normal moments are foundational for statistical methods. The derivation and simplification of these moments are critical for the accuracy of various statistical estimates and analyses.
Christopher Stroude Withers
doaj   +1 more source

Price Indices Rekindled, 1970s–1990s: Theory and Practice at Cross Purposes?

Journal of Economic Surveys, Volume 40, Issue 2, Page 898-914, April 2026.
ABSTRACT This paper revisits the discussions on price indices during a period marked by theoretical advancements and practical challenges in measuring inflation. Index‐number theorists sought to improve accuracy, yet national statistical offices largely maintained established practices due to concerns over data availability, stability, and public trust.
Victor Cruz‐e‐Silva, Bert M. Balk
wiley   +1 more source