Results 31 to 40 of about 606,553 (265)
The Case of the Homogeneous Errors-In-Variables Model
Recently, it has been claimed that the HomogeneousErrors-In-Variables (HEIV) Model, where the lefthandside (LHS) vector is allowed to be multiplied withan unknown scale factor, would represent a generalizationof the regular EIV-Model for which a number ...
Schaffrin B., Snow K.
doaj +1 more source
Error-in-variables modelling for operator learning.
Deep operator learning has emerged as a promising tool for reduced-order modelling and PDE model discovery. Leveraging the expressive power of deep neural networks, especially in high dimensions, such methods learn the mapping between functional state variables. While proposed methods have assumed noise only in the dependent variables, experimental and
Patel, Ravi G. +3 more
openaire +2 more sources
ABSTRACT Introduction Adolescent siblings of children with cancer are at elevated risk for psychosocial problems. Unfortunately, various barriers such as limited family time and resources, conflicting schedules, and psychosocial staffing constraints at cancer centers hinder sibling access to support.
Christina M. Amaro +10 more
wiley +1 more source
Least squares regression with errors in both variables: case studies
Analytical curves are normally obtained from discrete data by least squares regression. The least squares regression of data involving significant error in both x and y values should not be implemented by ordinary least squares (OLS).
Elcio Cruz de Oliveira +1 more
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Errors-in-Variables Estimation with Wavelets
This paper proposes a wavelet (spectral) approach to estimate the parameters of a linear regression model where the regressand and the regressors are persistent processes and contain a measurement error. We propose a wavelet filtering approach which does not require instruments and yields unbiased estimates for the intercept and the slope parameters ...
Gençay, Ramazan, Gradojevic, Nikola
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Clinical Course and Impact of Breaks in Therapy for Children With Relapsed/Refractory Solid Tumors
ABSTRACT Introduction Pediatric relapsed or refractory (R/R) solid tumors carry a dismal prognosis, and postrelapse patient experiences are not well described. We present postrelapse outcomes, including number of R/R events and subsequent therapy regimens.
Matthew T. McEvoy +5 more
wiley +1 more source
ABSTRACT Background Neuropsychological complications may impair the qualitative prognosis of patients with pediatric brain tumors. However, multifaceted evaluations cannot be conducted in all patients because they are time consuming and burdensome for patients.
Ami Tabata +9 more
wiley +1 more source
Fitting an Equation to Data Impartially
We consider the problem of fitting a relationship (e.g., a potential scientific law) to data involving multiple variables. Ordinary (least squares) regression is not suitable for this because the estimated relationship will differ according to which ...
Chris Tofallis
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NONPARAMETRIC INSTRUMENTAL REGRESSION WITH ERRORS IN VARIABLES [PDF]
This paper considers nonparametric instrumental variable regression when the endogenous variable is contaminated with classical measurement error. Existing methods are inconsistent in the presence of measurement error. We propose a wavelet deconvolution estimator for the structural function that modifies the generalized Fourier coefficients of the ...
Adusumilli, Karun, Otsu, Taisuke
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ABSTRACT Background Parents of children treated for acute lymphoblastic leukemia (ALL) often experience significant caregiver burden and disruption to their well‐being. While parent quality of life (QoL) during treatment is well characterized, little is known about outcomes during early survivorship.
Sara Dal Pra +3 more
wiley +1 more source

