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26 articles for “Robust Regression”
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Research ArticleOpen accessIn the abstractPrevalence of Feline Leukemia Virus and Feline Immunodeficiency Virus in Patients from Veterinary Centers in Three Colombian CitiesAna Sofía Mejía-Villada, Maria José Arenas-González, Carolina Ríos Usuga et al.In Colombia, research on Feline Leukemia Virus (FeLV) and Feline Immunodeficiency Virus (FIV) is incipient, despite being the viruses of greatest clinical and epidemiological importance in domestic cats, presenting a worldwide distribution but with very variable prevalence. To determine the molecular prevalence of FeLV and FIV and their associated factors in domestic cats treated in veterinary centers in three Colombian … …American Journal of Animal and Veterinary Sciences, Vol. 19, Issue 3 · 11 Jun 2024 · 7,283 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Analysis of BMI and Liver Size on Kidney Function in Young Mexican American PopulationOrlando Patricio, Rohitha Goonatilake, Fernando G. Quintana et al.This study aimed todetermine the probability of fatty liver, hepatomegaly, and liver size ≥2SDwith age in each category of BMI percentile. It also aimed to investigate therelationship between GFR, BMI percentile, liver size, Blood Pressure (BP), andright kidney volume among overweight and obese boys and girls and to identifythe predictors of GFR. 763 records of boys and girls visiting a … …Journal of Mathematics and Statistics, Vol. 18, Issue 1 · 9 Sep 2022 · 5,540 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Empirical Study of Robust Modified Recursive Fits of Moving Average ModelsMohamed Ali Ismail, Hend A. Auda, Joe W. McKean, Mahmoud Mohamed SadekThe time-series Moving Average (MA) model is a nonlinear model; see, for example. For traditional Least Squares (LS) fits, there are several algorithms to use for computing its fit. Since the model is nonlinear, Fuller discusses a Newton-type step algorithm. proposed a recursive algorithm based on a sequence of three linear LS regressions. In this study, we robustify Koreisha and … …Journal of Mathematics and Statistics, Vol. 18, Issue 1 · 28 Jul 2022 · 5,859 accessesView PDFCite
Research ArticleOpen accessIn the abstractMeasurement of Cooling Load-Based Occupant Behavior in Under-Actuated Zones: A Time-Variance ApproachYaddarabullah, Yusuf Maulana Akbar, Aedah Binti Abd Rahman, Amna SaadThis research is dedicated to the enhancement of Heating, Ventilation, and Air-Conditioning (HVAC) systems through an innovative investigation of occupant behavior within under-actuated zones. These zones are strategically positioned to elevate indoor air quality and comfort through the intelligent utilization of HVAC systems. However, accurately measuring the cooling loads within these zones, which are inherently influenced by the presence of … …American Journal of Applied Sciences, Vol. 20, Issue 1 · 11 Dec 2023 · 6,158 accessesView PDFCite
Research ArticleOpen accessIn the abstractData Preparation in Machine Learning for Condition-based MaintenanceOns Masmoudi, Mehdi Jaoua, Amel Jaoua, Soumaya YacoutUsing Machine Learning (ML) prediction to achieve a successful, cost-effective, Condition-Based Maintenance (CBM) strategy has become very attractive in the context of Industry 4.0. In other fields, it is well known that in order to benefit from the prediction capability of ML algorithms, the data preparation phase must be well conducted. Thus, the objective of this paper is to investigate … …Journal of Computer Science, Vol. 17, Issue 6 · 4 Jun 2021 · 8,412 accessesView PDFCite
Research ArticleOpen accessIn the abstractQSAR Modeling of Thirty Active Compounds for the Inhibition of the Acetylcholinesterase EnzymeNour El Houda Hammoudi, Yacine Benguerba, Widad SobhiThis work aims at developing a reliable and predictive QSAR model which allows, on one hand, an exploration of the main molecular descriptors responsible for the inhibitory activity towards the Acetylcholinesterase enzyme and, on the other hand, predict the inhibitory activity of new compounds before testing them experimentally. This study involves a series of DL0410 and its 29 DL0410 derivatives. … …Current Research in Bioinformatics, Vol. 8, Issue 1 · 2 Mar 2020 · 11,426 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Interregional Freight Generation Modelling Methods by using Nationwide Commodity Flow Survey DataWirach HirunA trip generation model is one of the four parts of the classical transport planning model, which explores the volume of trip or freight at the originating and destination points of a traffic analysis zone. The process of calibrating a trip generation model needs appropriate data. Freight transport data are always robust and a powerful calibration technique is required to … …American Journal of Engineering and Applied Sciences, Vol. 9, Issue 3 · 18 Aug 2016 · 8,107 accessesView PDFCite
Research ArticleOpen accessIn the abstractMODEL SELECTION VIA ROBUST VERSION OF R-SQUAREDShokrya SalehR-squared (R2) is a popular method for variable selection in linear regression models. R2 based on Least Squares (LS) regression minimizes the sum of the squared residuals; LS is sensitive to outlier observation. Alternative criterion based on M-estimators, which is less sensitive to outlying observation has been proposed. In this study explicit expression for such criterion is obtained when the … …Journal of Mathematics and Statistics, Vol. 10, Issue 3 · 9 Oct 2014 · 7,460 accessesView PDFCite
Research ArticleOpen accessIn the abstractA NOVEL ROBUST AND EFFICIENT TOOL FOR DETECTING HETEROSCEDASTICITYWei Xiong, Maozai TianOne of the greatest values of Quantile Regression (QR) is that it provides a good procedure in the sense that QR could be much more efficient and sometimes arbitrarily more efficient in recovering the mean function than the Least Squares (LS) even when without moment conditions. However, heteroscedasticity definitely causes conditional variances of parametric or nonparametric estimates of mean functions … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 21 Mar 2014 · 6,657 accessesView PDFCite
Research ArticleOpen accessIn the abstractAN EFFECTIVE TECHNIQUE OF MULTIPLE IMPUTATION IN NONPARAMETRIC QUANTILE REGRESSIONYanan Hu, Qianqian Zhu, Maozai TianIn this study, we consider the nonparametric quantile regression model with the covariates Missing at Random (MAR). Multiple imputation is becoming an increasingly popular approach for analyzing missing data, which combined with quantile regression is not well-developed. We propose an effective and accurate two-stage multiple imputation method for the model based on the quantile regression, which consists of initial imputation … …Journal of Mathematics and Statistics, Vol. 10, Issue 1 · 4 Jan 2014 · 6,813 accessesView PDFCite