Results 51 to 60 of about 1,688,491 (311)

Sequential linear regression with online standardized data. [PDF]

PLoS ONE, 2018
The present study addresses the problem of sequential least square multidimensional linear regression, particularly in the case of a data stream, using a stochastic approximation process.
Kévin Duarte, Jean-Marie Monnez, Eliane Albuisson   +2 more
doaj   +1 more source

Therapeutic Apheresis for Intravenous Methylprednisolone‐Refractory Neuromyelitis Optica Spectrum Disorder: Clinical and Radiological Outcomes in a Single‐Center Case Series

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Neuromyelitis optica spectrum disorder (NMOSD) is a relapsing autoimmune disease of the central nervous system. High‐dose intravenous methylprednisolone (IVMP) is the standard first‐line therapy for acute attacks, although some patients remain refractory.
Wataru Horiguchi, Daisuke Katagiri, Takeyuki Watadani, Shunichi Matsuda, Hiroshi Kaneko, Noritoshi Arai   +5 more
wiley   +1 more source

Heavy-Tailed Linear Regression and K-Means

Information
Most standard machine learning algorithms are formulated with the implicit assumption that empirical data are “well-behaved”. In this work, we consider heavy-tailed data whose underlying distribution does not necessarily possess finite moments.
Mario Sayde, Jihad Fahs, Ibrahim Abou-Faycal   +2 more
doaj   +1 more source

Dietary Protein Intake and Peritoneal Protein Losses in Peritoneal Dialysis Patients

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Introduction Peritoneal dialysis (PD) patients lose protein in their waste dialysate, potentially increasing their risk for malnutrition. We wished to determine whether there was any association between losses and dietary protein intake (DPI). Methods DPI was assessed from 24‐h dietary recall using Nutrics software.
Haalah Shaaker, Andrew Davenport
wiley   +1 more source

Neutrosophic Correlation and Simple Linear Regression [PDF]

Neutrosophic Sets and Systems, 2014
Since the world is full of indeterminacy, the neutrosophics found their place into contemporary research. The fundamental concepts of neutrosophic set, introduced by Smarandache.
A. A. Salama, O. M. Khaled, K. M. Mahfouz   +2 more
doaj  

Clustered Partial Linear Regression [PDF]

Machine Learning, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Luís Torgo, Joaquim Pinto da Costa
openaire   +2 more sources

Structural instability impairs function of the UDP‐xylose synthase 1 Ile181Asn variant associated with short‐stature genetic syndrome in humans

FEBS Letters, EarlyView.
The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li, Pedro A. Sánchez‐Murcia, Bernd Nidetzky   +2 more
wiley   +1 more source

Kernel Density Estimated Linear Regression

Proceedings of the International Florida Artificial Intelligence Research Society Conference
Regression analysis is a cornerstone of predictive modeling, with linear regression and kernel regression standing as two of its most prominent paradigms.
Roshan Kalpavruksha, Rohan Kalpavruksha, Teryn Cha, Sung-Hyuk Cha   +3 more
doaj   +1 more source

O ajuste de funções matemáticas a dados experimentais Curve fitting of mathematical functions to experimental data

Química Nova, 1997
The least square method is analyzed. The basic aspects of the method are discussed. Emphasis is given in procedures that allow a simple memorization of the basic equations associated with the linear and non linear least square method, polinomial ...
Rogério Custodio, João Carlos de Andrade, Fábio Augusto   +2 more
doaj   +1 more source

Double F-Class Predictors in Linear Regression Models [PDF]

The Egyptian Statistical Journal, 1993
This article develops a family of biased predictors, namely the double f-Class, in the linear regression model. Employing the small disturbance approach, I study the bias and mean square error of the double f-Class predictor.
G. Ghazal
doaj   +1 more source