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229 results for “regression method”
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Research ArticleOpen accessIn the abstractComparison of Collinearity Indices for Linear Models in Agricultural TrialsDanny Villegas Rivas, José M. Palacios Sánchez, Cristina A. Alzamora Rivero et al.The deleterious consequences of collinearity in linear regression on the precision of estimators of regression coefficients and the interpretability of the fitted model are widely recognized. In this study, we compare several methodologies for assessing collinearity in linear models and explore the effect of outliers on collinearity. The robustness of collinearity measures (individual and overall) is validated through two detailed … …OnLine Journal of Biological Sciences, Vol. 24, Issue 2 · 28 Dec 2023 · 6,491 accessesView PDFCite
Research ArticleOpen accessIn the abstractParameter Calibration of Soil in the Poyang Lake Region Based on Discrete Element MethodBaoyu Zhu, Jun’an Liu, Xiongfei Chen et al.In order to obtain the soil parameters of Poyang Lake Region before direct seeding, the soil properties of Duchang County, Poyang County and Xinjian District recollected and the discrete element method model is established. The angle of repose of paddy soil is 53.00° tested by the lateral wall collapse method. Eleven parameters are used to establish EDEM simulation model with … …American Journal of Biochemistry and Biotechnology, Vol. 16, Issue 4 · 16 Dec 2020 · 6,377 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of a Beta Regression Model for Covariate Adjusted ROCXing Meng, J.D. TubbsThe Receiver Operating Characteristic (ROC) curve and the area under the ROC (AUC) are widely used in determining the diagnostic capability of a binary classification procedure. Since the test performance is affected by covariates, the ROC and AUC have been utilized in a Generalized Linear Regression (GLM) setting. In this study, we revisit a problem where the AUC regression model … …Current Research in Biostatistics, Vol. 10, Issue 1 · 18 Jun 2020 · 13,966 accessesView PDFCite
Research ArticleOpen accessIn the abstractTilted Beta Binomial Linear Regression Model: A Bayesian ApproachEdilberto Cepeda-Cuervo, Maria Victoria Cifuentes-AmadoThis paper proposes new linear regression models to deal with overdispersed binomial datasets. These new models, called tilted beta binomial regression models, are defined from the tilted beta binomial distribution, proposed assuming that the parameter of the binomial distribution follows a tilted beta distribution. As a particular case of this regression models, we propose the beta rectangular binomial regression models, … …Journal of Mathematics and Statistics, Vol. 16, Issue 1 · 5 Jan 2020 · 8,784 accessesView PDFCite
Research ArticleOpen accessIn the abstractDefect Classification of Reinforced Concrete Structures with Nondestructive Tests Using Statistical and Machine Learning MethodsSajjad Sayyar-Roudsari, Armaghan Shalbaftabar, Farshid Damirchilo et al.In this study, twelve reinforced concrete beams were constructed, each with specified dimensions and initial compressive strength. The beams were divided into four groups: A control group without any defect, a void group featuring a centrally located void, a corrosion group and a debonding group. The impact echo test was used for nondestructive testing, gathering data on compressive and shear … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 3 · 11 Jun 2024 · 5,258 accessesView PDFCite
Research ArticleOpen accessIn the abstractHigh Accurate Multicriteria Cluster-Based Collaborative Filtering Recommender SystemZhila Yaseen Taha, Sadegh Abdollah AminifarA Recommender System (RS) is one of the appropriate answers by researchers for alleviating the problem of customers' overload with information from an internet source. In RS, users' evaluation of the items assists in quickly determining the user's preferences and removing the choosing overhead for the user the next time they search. However, using user ratings for an item based … …Journal of Computer Science, Vol. 18, Issue 12 · 10 Dec 2022 · 5,914 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Study of the Effects of Soil Salinity on the Growth and Development of Maize (Zea Mays L.) by using Sentinel-2 ImageryShakhislam Uzakbaevich Laiskhanov, Zhassulan Maratuly Smanov, Kulyash Duisenbaevna Kaimuldinova et al.Salinization of soil cover and the constant increase in their area have become one of the most pressing problems year after year for irrigated agriculture regions. The degradation processes caused by the salinity of soils negatively affect the growth and development of food crops. Therefore, this study focused on the effects of soil salinity in the midstream of the Syrdarya … …OnLine Journal of Biological Sciences, Vol. 22, Issue 3 · 15 Aug 2022 · 6,257 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomated Evaluation of Short Answers Using Text Similarity for the Portuguese LanguageSilvério Sirotheau, Joao C.A. dos Santos, Eloi L. Favero, Simone N. de FreitasAlong with the development of distance education, emerges the demand for virtual environments as the automated evaluation studies of essays that has already produced promising results. However, when dealing with short answers, replicating the decisions of a human grader is still a challenge, as the portability of essay evaluation techniques to short answers has not produced results with the same … …Journal of Computer Science, Vol. 15, Issue 11 · 21 Nov 2019 · 6,899 accessesView PDFCite
Research ArticleOpen accessIn the abstractModel Comparison for the Prediction of Stock Prices in the NYSEVictoria Switlyk, Junfeng ShangThe stock market is an integral part of investments as well as the economy. The prediction of stock prices is an exciting and challenging problem that has been considered by many due to the complexity and noise within the market and to the potential profit that can be yielded from accurate predictions. We aim to construct and compare models used … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 26 Sep 2019 · 7,475 accessesView PDFCite
Research ArticleOpen accessIn the abstractSubset ARMA Model Identification for Monthly Electricity Consumption DataAmaal El Sayed Abd El Ghany MubarakSubset models can always be highly influential in series analysis, particularly when the data demonstrate a sort of form in periodic behavior with miscellaneous natural period's ranges, specifically; days, weeks, months and years. Subset models can also be effective as they let the number of parameters lower allowing only the really needed ones to be present in the model. Though … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 8 Mar 2019 · 7,140 accessesView PDFCite