Results 31 to 40 of about 1,688,491 (311)
Transportes, 2020 Estimating the number of trips generated by a company is an essential part of the process of freight demand modelling. In this context, the current study examines freight trip generation to buildings under construction (BUC) using generalised linear ...
Leise Kelli de Oliveira +3 more
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Using Simulation In Teaching Simple Linear Regression [PDF]
مجلة جامعة الانبار للعلوم الصرفة, 2012 This paper aims to use simulation in teaching simple linear regression, computer stimulation can be used to teach complicated statistical concepts in linear regression more quickly and effectively than traditional lecture alone.
ALBRIA A., ISAM K. ALANI, AHMED H. ALANI
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Distributed Online Linear Regressions
IEEE Transactions on Information Theory, 2021 We study online linear regression problems in a distributed setting, where the data is spread over a network. In each round, each network node proposes a linear predictor, with the objective of fitting the \emph{network-wide} data. It then updates its predictor for the next round according to the received local feedback and information received from ...
Deming Yuan +2 more
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Partially linear censored quantile regression [PDF]
, 2009 Censored regression quantile (CRQ) methods provide a powerful and flexible approach to the analysis of censored survival data when standard linear models are felt to be appropriate.
Portnoy, S., Neocleous, T.
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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 +2 more
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Clustered linear regression [PDF]
Knowledge-Based Systems, 2002 Clustered linear regression (CLR) is a new machine learning algorithm that improves the accuracy of classical linear regression by partitioning training space into subspaces. CLR makes some assumptions about the domain and the data set. Firstly, target value is assumed to be a function of feature values.
Ari, B., Güvenir H.A.
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Multiple Linear Regression versus Automatic Linear Modelling
Arquivo Brasileiro de Medicina Veterinária e ZootecniaIn 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
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CoRR, 2015 We consider the problem of fitting a linear model to data held by individuals who are concerned about their privacy. Incentivizing most players to truthfully report their data to the analyst constrains our design to mechanisms that provide a privacy guarantee to the participants; we use differential privacy to model individuals' privacy losses.
Cummings, Rachel +2 more
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Linear Regression with Censoring
Journal of Multivariate Analysis, 1994 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Srinivasan, C., Zhou, M.
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Osteosarcoma (OS) and Ewing sarcoma (EWS) are the most common primary bone cancers in children, but acute thrombosis is poorly characterized in this population. Our study evaluated the rates of venous thromboembolism (VTE) and associated risk factors in pediatric patients with bone sarcomas treated over a 10‐year period encompassing
Sarah Kappa +8 more
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