Results 61 to 70 of about 3,495,066 (309)
Journal of Water and Climate Change, 2023 The present study on the hydrologic regionalization was taken up to evaluate the utility of hierarchical cluster analysis for the delineation of hydrologically homogeneous regions and multiple linear regression (MLR) models for information transfer to ...
Chandrashekarayya G. Hiremath +1 more
doaj +1 more source
Low rank multivariate regression [PDF]
Electronic Journal of Statistics, 2011 We consider in this paper the multivariate regression problem, when the target regression matrix $A$ is close to a low rank matrix. Our primary interest in on the practical case where the variance of the noise is unknown. Our main contribution is to propose in this setting a criterion to select among a family of low rank estimators and prove a non ...
openaire +3 more sources
Applied Multivariate Research, v.12 no.3 (complete version)
, 2007 The third issue of Applied Multivariate Research edited by Dennis L. JacksonThe article "Cluster analysis and rankings of Canadian universities: Misadventures with rank-based data and implications for the welfare of students" by Kenneth M.
core +1 more source
Predictive Ability of Plasma p‐tau217 for β‐Amyloid Status: A Prospective Multicenter Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Plasma tau phosphorylated at threonine 217 (p‐tau217) measured with fully automated platforms has shown high accuracy for Alzheimer's disease (AD) diagnosis, but real‐world multicenter data remain limited. We aimed to validate the diagnostic performance of p‐tau217 for identifying AD pathology in a real‐world multicenter cohort ...
Miquel Massons +33 more
wiley +1 more source
Multivariate Analysis with Linearizable Regressions [PDF]
Psychometrika, 1988 We study the class of multivariate distributions in which all bivariate regressions can be linearized by separate transformation of each of the variables. This class seems more realistic than the multivariate normal or the elliptical distributions, and at the same time its study allows us to combine the results from multivariate analysis with optimal ...
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Multivariate-Cox regression analysis of the cohort survival.
, 2023 Multivariate-Cox regression analysis of the cohort survival.
Yue Hu (201714) +4 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives Acute kidney injury (AKI) is a common but often underrecognized complication in ischemic stroke patients undergoing mechanical thrombectomy, particularly among those with pre‐existing renal impairment. This study evaluated the incidence, risk factors, and clinical impact of AKI in this high‐risk population.
Michał Borończyk +10 more
wiley +1 more source
Adaptive Multivariate Ridge Regression
The Annals of Statistics, 1980 A multivariate version of the Hoerl-Kennard ridge regression rule is introduced. The choice from among a large class of possible generalizations is guided by Bayesian considerations; the result is implicitly in the work of Lindley and Smith although not actually derived there.
Brown, P. J., Zidek, J. V.
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To evaluate the efficacy and safety of ofatumumab in patients with myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD), and compare it with rituximab. Methods We conducted a single–center, observational study including 22 MOGAD patients treated with ofatumumab and 21 treated with rituximab.
Yuxin Fan +5 more
wiley +1 more source
Regression Models for Multivariate Count Data [PDF]
Journal of Computational and Graphical Statistics, 2017 Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing.
Zhang, Yiwen +3 more
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