Results 91 to 100 of about 232,548 (306)
A Comparison of Data-driven Partial Least Squares to Existing Partial Least Squares Models
, 2022 https://rdc.reed.edu/v1/resources/5f77ac57-1066-4805-90e9-329b7a61d704/thumb/128.jpgData-driven sparse partial least squares is a recently proposed sparse partial least squares method seeking to improve on existing methodology. Data-driven sparse partial
Lee, Harpeth
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Five‐Year Disease Progression in Synuclein Seeding Positive Sporadic Parkinson's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To provide a comprehensive description of disease progression in synuclein seeding assay (SAA) positive sporadic Parkinson Disease participants, using Neuronal Synuclein Disease integrated biological and functional impairment staging framework.
Paulina Gonzalez‐Latapi +19 more
wiley +1 more source
Value of MRI Outcomes for Preventive and Early‐Stage Trials in Spinocerebellar Ataxias 1 and 3
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To examine the value of MRI outcomes as endpoints for preventive and early‐stage trials of two polyglutamine spinocerebellar ataxias (SCAs). Methods A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene‐negative controls) was scanned at 3T up ...
Thiago J. R. Rezende +26 more
wiley +1 more source
Group‐wise partial least square regression
Journal of Chemometrics, 2017 AbstractThis paper introduces the group‐wise partial least squares (GPLS) regression. GPLS is a new sparse PLS technique where the sparsity structure is defined in terms of groups of correlated variables, similarly to what is done in the related group‐wise principal component analysis. These groups are found in correlation maps derived from the data to
José Camacho, Edoardo Saccenti
openaire +5 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Accessing brain magnetic resonance imaging (MRI) can be challenging, especially for underserved patients, which may lead to disparities in neurological diagnosis. Method This mixed‐methods study enrolled adults with one of four neurological disorders: mild cognitive impairment or dementia of the Alzheimer type, multiple sclerosis ...
Maya L. Mastick +19 more
wiley +1 more source
Non-Metric Partial Least Squares
Electronic Journal of Statistics, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +3 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background and Objectives Multiple sclerosis (MS) exhibits racially disparate rates of disease progression. Black people with MS (B‐PwMS) experience a more severe disease course than non‐Hispanic White people with MS (NHW‐PwMS). Here we investigated structural and functional connectivity as well as structure–function decoupling in the ...
Emilio Cipriano +11 more
wiley +1 more source
Short-Term Load Forecasting with Tensor Partial Least Squares-Neural Network
Energies, 2019 Short-term load forecasting is very important for power systems. The load is related to many factors which compose tensors. However, tensors cannot be input directly into most traditional forecasting models.
Yu Feng, Xianfeng Xu, Yun Meng
doaj +1 more source
On the equivalence between Total Least Squares and Maximum Likelihood PCA
, 2005 The maximum likelihood PCA (MLPCA) method has been devised in chemometrics as a generalization of the well-known PCA method in order to derive consistent estimators in the presence of errors with known error distribution.
Wentzell, P. +7 more
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Tide modeling using partial least squares regression
, 2020 This research explores the novel use of the partial least squares regression (PLSR) as an alternative model to the conventional least squares (LS) model for modeling tide levels. The modeling is based on twenty tidal constituents: M2, S2, N2, K1, O1, MO3,
Ndehedehe, Christopher +2 more
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