Ohyver, Margaretha (2013) PENERAPAN METODE TRANSFORMASI LOGARITMA NATURAL DAN PARTIAL LEAST SQUARES UNTUK MEMPEROLEH MODEL BEBAS MULTIKOLINIER DAN OUTLIER. Jurnal Mat Stat, 13 (01). pp. 4251. ISSN 14121220

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Abstract
Multicollinear and outlier occur when making regression modeling. Multicollinear leads difficulty in separating the influence of each independent variable on the response variable. Outlier causes unmet assumption of normality in the regression. Both cases occur in the number of hotel visitors in Kendari. The purpose of this paper is to find a model that is free from multicollinear and outlier. Using the natural logarithm transformation and partial least squares, obtained model has the value of variance inflation factor less than ten and is able to overcome the outlier.
Item Type:  Article 

Subjects:  MATHEMATICAL ANALYSIS LINEAR PROGRAMMING MATHEMATICS & STATISTICS 
Depositing User:   Anindito 
Date Deposited:  18 Apr 2013 04:42 
Last Modified:  18 Apr 2013 04:42 
URI:  http://eprints.binus.ac.id/id/eprint/25629 
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