Results 21 to 30 of about 1,234,185 (150)

Multiple Linear Regression versus Automatic Linear Modelling

Arquivo Brasileiro de Medicina Veterinária e Zootecnia
In this study, performances of Multiple Linear Regression and Automatic Linear Modelling are compared for different sample sizes and number of predictors. A comprehensive Monte Carlo simulation study was carried out for this purpose.
S. Genç, M. Mendeş
doaj   +1 more source

Sparse Semi-Functional Partial Linear Single-Index Regression

Proceedings, 2018
The variable selection problem is studied in the sparse semi-functional partial linear model, with single-index type influence of the functional covariate in the response. The penalized least squares procedure is employed for this task.
Silvia Novo, Germán Aneiros, Philippe Vieu   +2 more
doaj   +1 more source

Fuzzy Linear Regression of Rainfall-Altitude Relationship

Proceedings, 2018
Classical linear regression has been used to measure the relationship between rainfall data and altitude in different meteorological stations, in order to evaluate a linear relation.
Christos Tzimopoulos, Christos Evangelides, Christos Vrekos, Nikiforos Samarinas   +3 more
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Consequences of ignoring clustering in linear regression

BMC Medical Research Methodology, 2021
Background Clustering of observations is a common phenomenon in epidemiological and clinical research. Previous studies have highlighted the importance of using multilevel analysis to account for such clustering, but in practice, methods ignoring ...
Georgia Ntani, Hazel Inskip, Clive Osmond, David Coggon   +3 more
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Hybrid principal component regression estimation in linear regression

Electronic Research Archive
In this paper, the principal component regression (PCR) estimators for regression parameters were studied in a linear regression model. After discussing the advantages and disadvantages of the classical PCR, we put forward three versions of hybrid PCR ...
Jian-Ying Rong , Xu-Qing Liu
doaj   +1 more source

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

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

Synthetic Control As Online Linear Regression [PDF]

, 2022
Jiafeng Chen
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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  

Differentially Private Distributed Bayesian Linear Regression with MCMC [PDF]

, 2023
Barış Alparslan, Sinan Yıldırım, Ş. İlker Birbil   +2 more
openalex   +1 more source