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229 results for “regression method”

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Research ArticleOpen accessIn the abstractGENERALIZED REGRESSION NEURAL NETWORK BASED EXPERT SYSTEM FOR HEPATITIS B DIAGNOSISC. Mahesh, E. Kannan, M. S. SaravananHepatitis B is a potentially life-threatening liver infection caused by the hepatitis B virus. The virus interferes with the function of the liver while replicating in hepatocytes. It is a major global health problem and the most serious type of viral hepatitis. Chronic liver disease is caused by viral hepatitis and putting people at high risk of death from cirrhosis … …Journal of Computer Science, Vol. 10, Issue 4 · 3 Dec 2013 · 6,985 accessesView PDFCite
Research ArticleOpen accessIn the abstractSMOOTHING SPLINE IN SEMIPARAMETRIC ADDITIVE REGRESSION MODEL WITH BAYESIAN APPROACHRita Diana, I. Nyoman Budiantara, Purhadi, Satwiko DarmestoSemiparametric additive regression model is a combination of parametric and nonparametric regression models. The parametric components are not linear but following a polynomial pattern, while the nonparametric components are unknown pattern and assumed to be contained in the Sobolev space. The nonparametric components can be approximated by smoothing spline functions. In the development of smoothing spline, the classical statistical approach … …Journal of Mathematics and Statistics, Vol. 9, Issue 3 · 12 Jun 2013 · 7,254 accessesView PDFCite
Research ArticleOpen accessIn the abstractMeasurement of Fibrinogen Concentration in the Plasma of Dogs: A Comparison Between Heat Precipitation and Modified Thrombin Clotting Time MethodLabrini V. Athanasiou, Theodoros A. Petanides, Manolis K. Chatzis, Manolis N. SaridomichelakisFibrinogen is a glycoprotein that plays a key role in blood clotting and is also a non-specific indicator of inflammation. The most widely used techniques for measuring plasma fibrinogen concentration include heat precipitation (Millar’s technique) and modified thrombin clotting time (Clauss method). Both techniques have been automated in a haematology analyzer (QBC-Vet Autoreader®, IDEXX; Millar’s technique) and in a newly … …American Journal of Animal and Veterinary Sciences, Vol. 8, Issue 2 · 18 May 2013 · 7,453 accessesView PDFCite
Research ArticleOpen accessIn the abstractOn Multiresponse Semiparametric Regression ModelSri Haryatmi, I. Nyoman Budiantara, Wahyu WibowoThe modeling between predictors and response in statistics sometimes deals with more than one response or multiresponse situation. Furthermore, it can be happen that some predictors have linear relationship with the responses and the others predictor have unknown relationship. To overcome this modeling problem we proposed multiresponse semiparametric regression model. This model has more than one response and contains both … …Journal of Mathematics and Statistics, Vol. 8, Issue 4 · 20 Feb 2013 · 7,071 accessesView PDFCite
Research ArticleOpen accessIn the abstractParameter Estimation and Determination of Sample Size in Logistic RegressionAdeleke Kazeem Adedayo, Dawud Adebayo AgunbiadeThe determination of Sample-Size is often an important step in planning a statistical study and it is usually a difficult task. Among the important hurdles to be surpassed, one must obtain an estimate of one or more error variances and specify an effective sample size of importance. The study was carried out to check for the estimation of parameter and … …Journal of Mathematics and Statistics, Vol. 8, Issue 4 · 4 Feb 2013 · 6,918 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance of Multiple Linear Regression and Nonlinear Neural Networks and Fuzzy Logic Techniques in Modelling House PricesSiti Amri, Gurudeo Anand TularamHouse price prediction continues to be important for government agencies insurance companies and real estate industry. This study investigates the performance of house sales price models based on linear and non-linear approaches to study the effects of selected variables. Linear stepwise Multiple Regression (MR) and nonlinear models of Neural Network (NN) and Adaptive Neuro-Fuzzy (ANFIS) are developed and compared. The … …Journal of Mathematics and Statistics, Vol. 8, Issue 4 · 18 Dec 2012 · 8,434 accessesView PDFCite
Research ArticleOpen accessIn the abstractSpline Smoothing for Multi-Response Nonparametric Regression Model in Case of Heteroscedasticity of VarianceBudi Lestari, I. Nyoman Budiantara, Sony Sunaryo, Muhammad MashuriProblem statement: Assume that data (yki, tki), k = 1,2,…, p; i = 1,2,…,nk where nk represents the number of repeated measurement of kth object follows multi-response nonparametric regression model with variances of errors are heteroscedastic. Nonparametric regression curves are unknown and assumed to be smooth which are contained in Sobolev space. Random Errors are independent and normally distributed with … …Journal of Mathematics and Statistics, Vol. 8, Issue 3 · 13 Oct 2012 · 7,960 accessesView PDFCite
Research ArticleOpen accessIn the abstractDesign of Square Substrate Integrated Waveguide Cavity Resonators: Compensation of Modelling Errors by Support Vector Regression MachinesGiovanni AngiulliThe design of Substrate Integrated Waveguide (SIW) resonators is usually a cumbersome process, especially due to the length &#34trial and error&#34 procedure involved in this task. In this study Support Vector Regression Machines (SVRMs) are employed to compensate the modeling errors associated to the design of SIW rectangular cavity resonators. To validate the proposed approach, we have compared the design … …American Journal of Applied Sciences, Vol. 9, Issue 11 · 5 Sep 2012 · 6,695 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Gaussian Process Regression Model for the Traveling Salesman ProblemWanatchapong Kongkaew, Juta PichitlamkenProblem statement: Traveling Salesman Problem (TSP) is a famous NP hard problem. Many approaches have been proposed up to date for solving TSP. We consider a TSP tour as a dependent variable and its corresponding distance as an independent variable. If a predictive function can be formulated from arbitrary sample tours, the optimal tour may be predicted from this function. … …Journal of Computer Science, Vol. 8, Issue 10 · 30 Aug 2012 · 7,373 accessesView PDFCite
Research ArticleOpen accessIn the abstractNeural Networks Based Nonlinear Time Series Regression for Water Level Forecasting of Dungun RiverSiti Hajar Arbain, Antoni WibowoThe Department of Irrigation and Drainage (DID) Malaysia and Meteorological Malaysia Department (MMD) has been measured the flood characteristics benchmark which included water level, area inundation, peak inundation, peak discharge, volume of flow and duration of flooding. In terms of water levels, DID have introduced three categories of critical level stages namely normal, alert and danger levels. One of the … …Journal of Computer Science, Vol. 8, Issue 9 · 13 Aug 2012 · 7,800 accessesView PDFCite