1. Repository Universitas Jember
  2. LECTURER SCIENTIFIC PUBLICATION (Publikasi Ilmiah)
  3. Karya Deposit Ilmiah
  4. Fakultas Matematika & Ilmu Pengetahuan Alam
Please use this identifier to cite or link to this item: https://repository.unej.ac.id/xmlui/handle/123456789/56811
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dc.contributor.authorYuliani Setia Dewi-
dc.date.accessioned2014-04-10T04:26:56Z-
dc.date.available2014-04-10T04:26:56Z-
dc.date.issued2014-04-10-
dc.identifier.urihttp://repository.unej.ac.id/handle/123456789/56811-
dc.description.abstractCorrelation between predictor variables (multicollinearity) become a problem in regression analysis. There are some methods to solve the problem. Each method has complexity. One of those methods is PLS. This research aims to describe the procedur of Estimation of PLS regression. PLS combine principal component analysis and multiple linear regression. PLS method estimates regression coefficient by selecting the number of component that is used in the model that has optimum Mean Square Error (minimum MSE). Optimal MSE is taken from cross validation.en_US
dc.language.isootheren_US
dc.relation.ispartofseriesMajalah Ilmiah Matematika dan Statistika;Volume 9, Juni 2009-
dc.subjectPLS, multicollinearity, MSE, cross validationen_US
dc.titlePENDUGAAN KOEFISIEN REGRESI UNTUK DATA MENGANDUNG MULTIKOLINEARITAS MENGGUNAKAN PLSen_US
dc.typeArticleen_US
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