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329 results for “Regression model”
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Research ArticleOpen accessPhrase in the titleOn Regression Modeling of Human Immunodeficiency Virus PatientsHadeel Salim AL-KutubiProblem statement: The main propose of this study was to evaluate the HIV patients for the period 1990-2008 depend on three variables age, gender and ethnicity. Approach: The data was analyzed using regression and correlation methods to get the mathematical model that explain the relationship and the effect between the age, gender and ethnicity. SSPS program V. 17.0 was used … …American Journal of Applied Sciences, Vol. 6, Issue 8 · 31 Aug 2009 · 6,413 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleLinear Regression Model Selection Based on Robust Bootstrapping TechniqueHassan S. Uraibi, Habshah Midi, Bashar A. Talib, Jabar H. YousifProblem statement: Bootstrap approach had introduced new advancement in modeling and model evaluation. It was a computer intensive method that can replace theoretical formulation with extensive use of computer. The Ordinary Least Squares (OLS) method often used to estimate the parameters of the regression models in the bootstrap procedure. Unfortunately, many statistics practitioners are not aware of the fact that … …American Journal of Applied Sciences, Vol. 6, Issue 6 · 30 Jun 2009 · 7,876 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleExistence and Uniqueness Conditions for the Maximum Likelihood Solution In Regression Models For Correlated Bernoulli Random VariablesDavid Todem, KyungMann KimWe give sufficient and necessary conditions for the existence of the maximum likelihood estimate in a class of multivariate regression models for correlated Bernoulli random variables. The models use the concept of threshold crossing technique of an underlying multivariate latent variable with univariate components formulated as a linear regression model. However, in place of their Gaussian assumptions, any specified distribution … …Journal of Mathematics and Statistics, Vol. 3, Issue 3 · 30 Sep 2007 · 6,838 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleSpline Estimator for Bi-Responses and Multi-Predictors Nonparametric Regression Model in Case of Longitudinal DataAdji Achmad Rinaldo Fernandes, I Nyoman Budiantara, Bambang Widjanarko Otok, SuhartonoNonparametric regression approach is used when the shape of the curve regression is unknown. The spline estimator approach for longitudinal data can accommodate the correlation between observations within the same subject, which is not found in the cross-section data, so that the autocorrelation assumption problem can be resolved. On the other hand, with bi-responses approach, it will accommodate any correlation … …Journal of Mathematics and Statistics, Vol. 11, Issue 2 · 8 Oct 2015 · 7,337 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSoft Sensor Modeling of Product Concentration in Glutamate Fermentation using Gaussian Process RegressionRongjian Zheng, Feng PanThe on-line control of glutamate fermentation process is difficult, owing to the typical uncertainties of biochemical process and the lack of suitable on-line sensors for primary process variables. A prediction model based on Gaussian Process Regression (GPR) is presented to predict glutamate concentration online. First, Partial Least Squares (PLS) is applied to extract the features of the input secondary variables … …American Journal of Biochemistry and Biotechnology, Vol. 12, Issue 3 · 17 Sep 2016 · 7,663 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Soft Sensor Modelling of Biomass Concentration during Fermentation using Accurate Incremental Online v-Support Vector Regression Learning AlgorithmBinjie Gu, Feng PanIn order to model real fermentation process, a soft sensor modelling of biomass concentration during fermentation using accurate incremental online ν-Support Vector Regression (ν-SVR) learning algorithm was proposed. Firstly, an accurate incremental online ν-SVR learning algorithm was proposed. This algorithm solved the two complications introduced in the dual problem based on the equivalent formulation of ν-SVR. Moreover, it addressed the … …American Journal of Biochemistry and Biotechnology, Vol. 11, Issue 3 · 8 Aug 2015 · 7,327 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleForecasting River Flow in the USA: A Comparison between Auto-Regression and Neural Network Non-Parametric ModelsAbdel K.M. Baareh, Alaa F. Sheta, Khaled A. KhnaifesForecasting a time series became one of the most challenging tasks to variety of data sets. The existence of large number of parameters to be estimated and the effect of uncertainty and outliers in the measurements makes the time series modeling too complicated. Recently, Artificial Neural Network (ANN) became quite successful tool to handle time series modeling problem. This paper … …Journal of Computer Science, Vol. 2, Issue 10 · 31 Oct 2006 · 6,962 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFeasibility of Hybrid Neuro-Fuzzy (ANFIS) Machine Learning Model with Classical Multi-Linear Regression (MLR) For the Simulation of Solar Radiation: A Case Study Abuja, NigeriaNajashi B. Gafai, Asia'u Talatu BelgoreThe extremely variable nature of solar radiation makes it difficult for solar power plants to keep up with predicted power output and demand curves. As a result, solar radiation simulation is crucial to the efficient design, administration, and operation of any solar power plant. With only partially satisfactory results, empirical models have been routinely employed in Nigeria to predict solar … …Energy Research Journal, Vol. 13, Issue 1 · 21 Jul 2022 · 10,032 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleLeast Absolute Deviation Regression and Least Squares for Modeling Retention Indices of Set Compounds Food and Pollutants of the EnvironmentFatiha Mebarki, Khadija Amirat, Salima Ali Mokhnach, Djellol MessadiConsidering the importance of the statistical analysis of regression in modeling based separately on study for Quantitative structure retention indices on Carbowax 20 M (ICw20M) and OV-101 columns (IOV-101) relationships (QSRR) are determined for 114 pyrazines. The detection of influential observations for the standard least squares regression model is a problem which has been extensively studied. Least Absolute Deviation regression … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 5 Jun 2017 · 7,424 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIntegrated Multiple Linear Regression-One Rule Classification Model for the Prediction of Stock Price TrendLock Siew Han, Md Jan NordinOne of the main problems of predicting stock price with regression approach is overfitting a model. An overfit model becomes tailored to fit the random noise in the dataset rather than reflecting the overall population. For this it is necessary to construct an integrated regression-classification model to approximate the true model for the entire population in the dataset. The proposed … …Journal of Computer Science, Vol. 13, Issue 9 · 18 May 2017 · 7,422 accessesView PDFCite