7 results for “Penalized Method”

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Research ArticleOpen accessIn the keywordsOptimization of Penalty Parameter in Penalized Nonlinear Canonical Correlation Analysis by using Cross-ValidationIsamu NagaiThere is Canonical Correlation Analysis (CCA) as a way to find a linear relationship between a pair of random vectors. However, CCA cannot find a nonlinear relationship between them since the method maximizes the correlation between linear combinations of the vectors. In order to find the nonlinear relationship, we convert the vectors through some known conversion functions like a kernel … …Journal of Mathematics and Statistics, Vol. 11, Issue 3 · 22 Dec 2015 · 7,661 accessesView PDF Cite

Research ArticleOpen accessIn the abstractTwo-Stage Estimation in Inverse Problems using Combined Wavelet Thresholding and Penalized Maximum LikelihoodRobert G Aykroyd, Hassan AljohaniInverse problems occur in a wide range of practical scientific investigations where the variables of interest are only observed indirectly, such as magnetic and seismic imaging in geophysics, electrical tomography in industrial process monitoring, or PET scanning in medicine. Linear inverse problems can be thought of as highly multivariate regression problems with strong multicollinearity where the aim is to interpret … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 29 Sep 2017 · 7,925 accessesView PDF Cite

Research ArticleOpen accessIn the abstractUnivariate 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 PDF Cite

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 · 7,068 accessesView PDF Cite

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 · 7,955 accessesView PDF Cite

Research ArticleOpen accessIn the abstractSpline 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 PDF Cite

Research ArticleOpen accessIn the abstractOn the Discretized Algorithm for Optimal Problems Constrained by Differential Equation with Real CoefficientsO. OlotuA discretized scheme, Discretized Continuous Algorithm (DCA), for solving constrained quadratic optimal control problems was developed to ease the computational cumbersomeness inherent in some existing algorithms, particularly, the Function Space A lgorithm (FSA) by replacing the integral by a series of summation. In order to accomplish this numerical scheme, we resort to a finite approximation of it by discretizing its … …Journal of Mathematics and Statistics, Vol. 3, Issue 4 · 31 Dec 2007 · 6,851 accessesView PDF Cite