@inproceedings{467f08174a7745cf88438dd11fb86277,

title = "Simulation study for biresponses nonparametric regression model using MARS",

abstract = "In statistical modeling, especially regression analysis, we can find relationship pattern between two responses with several predictors and both of responses are correlated each other. When the assumption of the pattern is unknown, then the regression parameters could be obtained by using biresponses nonparametric regression. One method that often used in nonparametric regression with single response is Multivariate Adaptive Regression Spline (MARS). This paper aims to know how ability of MARS in estimating biresponses nonparametric regression through simulation study on different sample size (n) and variance error (σ2). We use R-square and MSE as the goodness of fit criterion. Result shows that the smaller variance error gives better estimation than the bigger one, because it gives higher R-square and smaller MSE values. Whereas the variation of sample size gives small effect on the accuracy of the model, because the value of R-square and MSE in this case tend to be the same on different sample sizes.",

keywords = "MARS, MSE, R-square, biresponses, simulation",

author = "Ampulembang, {Ayub Parlin} and Otok, {Bambang Widjanarko} and Rumiati, {Agnes Tuti} and Budiasih",

note = "Publisher Copyright: {\textcopyright} 2016 AIP Publishing LLC.; 7th SEAMS UGM International Conference on Mathematics and Its Applications: Enhancing the Role of Mathematics in Interdisciplinary Research ; Conference date: 18-08-2015 Through 21-08-2015",

year = "2016",

month = feb,

day = "11",

doi = "10.1063/1.4940860",

language = "English",

series = "AIP Conference Proceedings",

publisher = "American Institute of Physics Inc.",

editor = "Yeni Susanti and Wijayanti, {Indah Emilia} and Kusumo, {Fajar Adi} and Aluicius, {Irwan Endrayanto}",

booktitle = "Proceedings of the 7th SEAMS UGM International Conference on Mathematics and Its Applications 2015",

}