Results 91 to 100 of about 876,733 (274)

Fast Multiway Partial Least Squares Regression

open access: yesIEEE Transactions on Biomedical Engineering, 2019
Multiway array decomposition has been successful in providing a better understanding of the structure underlying data and in discovering potentially hidden feature dependences serving high-performance decoder applications. However, the computational cost of multiway algorithms can become prohibitive, especially when considering large datasets ...
Camarrone, Flavio, Van Hulle, Marc M.
openaire   +2 more sources

Partial robust M-regression. [PDF]

open access: yes
Partial Least Squares (PLS) is a standard statistical method in chemometrics. It can be considered as an incomplete, or 'partial', version of the Least Squares estimator of regression, applicable when high or perfect multicollinearity is present in the ...
Croux, Christophe   +3 more
core  

On Fuzzy Regression Adapting Partial Least Squares [PDF]

open access: yes, 2011
Partial Least Squared (PLS) regression is a model linking a dependent variable y to a set of X (numerical or categorical) explanatory variables. It can be obtained as a series of simple and multiple regressions of simple and multiple regressions.
A. BASARAN   +2 more
core  

Predicting and Comparing the Subjective Health Experience of Older Cancer Survivors and Non‐Cancer Survivors: A Modeling Approach

open access: yesAging and Cancer, EarlyView.
This study underscores the significant influence of frailty and vitality on the subjective health experience of older cancer survivors with acceptance and control emerging as salient mediators. These findings affirm the conceptual and empirical robustness of the model highlighting its potential utility in shaping future interventions for older cancer ...
Damien S. E. Broekharst   +4 more
wiley   +1 more source

Robust Nonlinear Partial Least Squares Regression Using the BACON Algorithm

open access: yesJournal of Applied Mathematics, 2018
Partial least squares regression (PLS regression) is used as an alternative for ordinary least squares regression in the presence of multicollinearity. This occurrence is common in chemical engineering problems.
Abdelmounaim Kerkri   +2 more
doaj   +1 more source

Influence properties of partial least squares regression. [PDF]

open access: yes
Regression; Partial least squares; Least-squares; Squares; Squares regression;
Croux, Christophe   +2 more
core  

Implementing PLS for distance-based regression: computational issues [PDF]

open access: yes, 2006
Distance-based regression allows for a neat implementation of the Partial Least Squares recurrence. In this paper we address practical issues arising when dealing with moderately large datasets (n ~ 10^4) such as those typical of automobile insurance ...
Boj, Eva   +3 more
core   +1 more source

Post‐COVID Fatigue Is Associated With Reduced Cortical Thickness After Hospitalization

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Neuropsychiatric symptoms are among the most prevalent sequelae of COVID‐19, particularly among hospitalized patients. Recent research has identified volumetric brain changes associated with COVID‐19. However, it currently remains poorly understood how brain changes relate to post‐COVID fatigue and cognitive deficits.
Tim J. Hartung   +190 more
wiley   +1 more source

Will Memantine Exacerbate Seizures in People With Epilepsy? A Prospective Cohort Study

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate whether add‐on memantine would exacerbate seizures in people with epilepsy. Methods This was a prospective cohort study. People with epilepsy diagnosed with cognitive impairment were consecutively invited. Those who agreed were followed up for at least 24 weeks.
Peiyu Wang   +7 more
wiley   +1 more source

Revisiting Useful Approaches to Data-Rich Macroeconomic Forecasting [PDF]

open access: yes
This paper revisits a number of data-rich prediction methods, like factor models, Bayesian ridge regression and forecast combinations, which are widely used in macroeconomic forecasting, and compares these with a lesser known alternative method: partial ...
George Kapetanios, Jan J.J. Groen
core  

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