Results 91 to 100 of about 974,381 (216)
MathematicsPenalized regression estimators have become widely adopted alternatives to ordinary least squares while analyzing collinear data, despite introducing some bias. However, existing penalized methods lack universal superiority across diverse data conditions.
Muhammad Shakir Khan +1 more
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Bounded Perturbation Regularization for Linear Least Squares Estimation
IEEE Access, 2017 This paper addresses the problem of selecting the regularization parameter for linear least-squares estimation. We propose a new technique called bounded perturbation regularization (BPR). In the proposed BPR method, a perturbation with a bounded norm is
Tarig Ballal +2 more
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Bootstrapping the Mean Integrated Squared Error
Journal of Multivariate Analysis, 1993 Let \(X_ 1,\dots,X_ n\) be a sequence of i.i.d. real random variables from an unknown density \(f\). For a given kernel \(K\) and a bandwidth \(h>0\), denote with \(f_ h\) the associated Parzen-Rosenblatt estimator of \(f\). There exists a huge literature on how to choose \(h\) in an optimal way.
openaire +1 more source
Window Length Selection and Signal-Noise Separation and Reconstruction in Singular Spectrum Analysis [PDF]
In Singular Spectrum Analysis (SSA) window length is a critical tuning parameter that must be assigned by the practitioner. This paper provides a theoretical analysis of signal-noise separation and reconstruction in SSA that can serve as a guide to ...
D.S. Poskitt, Md Atikur Rahman Khan
core
Functional and Structural Evidence of Neurofluid Circuit Aberrations in Huntington Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Disrupted neurofluid regulation may contribute to neurodegeneration in Huntington disease (HD). Because neurofluid pathways influence waste clearance, inflammation, and the distribution of central nervous system (CNS)–delivered therapeutics, understanding their dysfunction is increasingly important as targeted treatments emerge.
Kilian Hett +8 more
wiley +1 more source
Gradient Estimation using Lagrange Interpolation Polynomials [PDF]
In this paper we use Lagrange interpolation polynomials to obtain good gradient estimations.This is e.g. important for nonlinear programming solvers.As an error criterion we take the mean squared error.This error can be split up into a deterministic and ...
Brekelmans, R.C.M. +3 more
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Vestibular Patient Journey: Insights From Vestibular Disorders Association (VeDA) Registry
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Vestibular symptoms impose a high burden of disability. Understanding real‐world diagnostic and treatment pathways can identify care gaps and guide interventions. We aimed to characterize symptom profiles, diagnostic trends, provider involvement, and treatment patterns in vestibular disorders.
Ali Rafati +10 more
wiley +1 more source
پژوهشهای ریاضی, 2018 Introduction According to the classic sampling theory, errors that are mainly considered in the estimations are sampling errors. However, most non-sampling errors are more effective than sampling errors in properties of estimators.
Leader Navaei, Rasoul Imaz
doaj
Asymptotic Prediction Mean Squared Error for Strongly Dependent Processes with Estimated Parameters [PDF]
In this paper we deal with the prediction theory of long memory processes. After investigating the general theory relating to convergence of moments of the nonlinear least squares estimators, we evaluate the asymptotic prediction mean squared error of ...
Naoya Katayama
core
Data Science Journal, 2009 This paper suggests a ratio-cum-product estimator of finite population mean using a correlation coefficient between study variate and auxiliary variate in stratified random sampling.
Rajesh Tailor
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