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All Journal IPTEK The Journal for Technology and Science
Pudji Ismartini
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Computer Science & IT

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The Jackknife Interval Estimation of Parametersin Partial Least Squares Regression Modelfor Poverty Data Analysis Pudji Ismartini; Sony Sunaryo; Setiawan Setiawan
IPTEK The Journal for Technology and Science Vol 21, No 3 (2010)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v21i3.42

Abstract

One of the major problem facing the data modelling at social area is multicollinearity. Multicollinearity can have significant impact on the quality and stability of the fitted regression model. Common classical regression technique by using Least Squares estimate is highly sensitive to multicollinearity problem. In such a problem area, Partial Least Squares Regression (PLSR) is a useful and flexible tool for statistical model building; however, PLSR can only yields point estimations. This paper will construct the interval estimations for PLSR regression parameters by implementing Jackknife technique to poverty data. A SAS macro programme is developed to obtain the Jackknife interval estimator for PLSR.
Co-Authors Setiawan Setiawan Sony Sunaryo