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27 articles for “Spline”
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Research ArticleOpen accessEvery word in the titleβ-Spline Estimation in a Semiparametric Regression Model with Nonlinear Time Series ErrorsJinhong You, Gemai Chen, Xian ZhouWe study the estimation problems for a partly linear regression model with a nonlinear time series error structure. The model consists of a parametric linear component for the regression coefficients and a nonparametric nonlinear component. The random errors are unobservable and modeled by a first-order Markov bilinear process. Based on a B-spline series approximation of the nonlinear component function, we … …American Journal of Applied Sciences, Vol. 2, Issue 9 · 30 Sep 2005 · 6,734 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleThe Benefits of Bezier, B-Spline Algorithm in the Industry WorldDjunaidy SantosoComputer Graphics is a science which is widely used in all fields, especially in the fied of Industries, companies, banking and even hospitals. In the aviation industries, marines and automotves, computer graphics with its latest technologies, can be used to solve graphical or imaging problems. Wherever images is involved, for eaxmple for patients' need in the hospitals, shipping engineers/designers or … …Journal of Computer Science, Vol. 11, Issue 1 · 24 Jan 2015 · 6,772 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSPLINE ACTIVATED NEURAL NETWORK FOR CLASSIFYING CARDIAC ARRHYTHMIAY. S. Kumaraswamy, R. Ganesh KumarElectro Cardiogram’s (ECG) biomedical signals characterizing cardiac anomalies are used for identifying cardiac arrhythmia. Irregular heartbeat-Arrhythmia-affects heart rate causing problems. Many methods, trying to simplify arrhythmia monitoring through automated detection, were developed over the years. ECG classification for arrhythmia is investigated in this paper based on soft computing techniques. RR interval are extracted from time series of the ECG and … …Journal of Computer Science, Vol. 10, Issue 8 · 9 Apr 2014 · 6,968 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSpline 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 · 7,955 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSpline Estimator in Multi-Response Nonparametric Regression Model with Unequal Correlation of ErrorsBudi Lestari, I. Nyoman Budiantara, Sony Sunaryo, Muhammad MashuriProblem statement: In many applications two or more dependent variables are observed at several values of the independent variables, such as at time points. The statistical problems are to estimate functions that model their dependences on the independent variables and to investigate relationships between these functions. Nonparametric regression model, especially smoothing splines provide powerful tools to model the functions which … …Journal of Mathematics and Statistics, Vol. 6, Issue 3 · 30 Sep 2010 · 8,168 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleNumerical Solution of Fourth Order Linear Ordinary Differential Equations by Cubic Spline Collocation Tau MethodO.A. Taiwo, O.M. OgunlaranProblem Statement: Many boundary value problems that arise in real life situations defy analytical solution; hence numerical techniques are desirable to find the solution of such equations. New numerical methods which are comparatively better than the existing ones in terms of efficiency, accuracy, stability, convergence and computational cost are always needed. Approach: In this study, we developed and applied three … …Journal of Mathematics and Statistics, Vol. 4, Issue 4 · 31 Dec 2008 · 6,985 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleComparison of Multivariate Adaptive Regression Splines and Classification Regression Tree for Prediction of Body Weight of Bapedi SheepMadumetja Cyril Mathapo, Ramaisela Barley Mthembu, Albino Joas Tsenane et al.The study aimed to compare the performance of multiple adaptive regression splines and classification regression trees for the prediction of the body weight of Bapedi sheep. A total of 100 Bapedi sheep aged between one and five years old of different sexes were employed. The study measured the following: Body Length (BL), Withers Height (WH), Heart Girth (HG), Rump Height … …American Journal of Animal and Veterinary Sciences, Vol. 19, Issue 3 · 12 Jul 2024 · 5,184 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Multi-Criteria Optimization Approach to Cam Curve Design Combining Different Splines Given by Fixed and Adjustable CheckpointsLéo Moussafir, Vigen ArakelianThis study proposes a multi-criteria design optimization of cam mechanisms. This approach is based on the multistage interconnection of different tools: MATLAB, ADAMS, and mode frontier. It consists of three main issues: (i) The polynomial representation of splines given by checkpoints defining the specific motion of the follower; (ii) The connection of these splines by different degrees of fitting in … …Journal of Mechatronics and Robotics, Vol. 7, Issue 1 · 24 Mar 2023 · 6,646 accessesView PDFCite
Research ArticleOpen accessIn the keywordsUnivariate Generalized Additive Models for Simulated Stationary and Non-Stationary Generalized Pareto DistributionMostafa Behzadi, Mohd Bakri Adam, Anwar FitriantoGeneralized additive models as a predictor in regression approaches, are made up over cubic spline basis and penalized regression splines. Despite of linear predictor in GLM, generalized additive models use a sum of smooth functions of covariates as a predictor. The data which are used in this study have generalized Pareto distribution and have been simulated by inversion method. The … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 3 Jun 2017 · 7,430 accessesView PDFCite
Research ArticleOpen accessIn the keywordsOn 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 · 7,068 accessesView PDFCite