The Jackknife Interval Estimation of Parameters in Partial Least Squares Regression Model for Poverty Data Analysis  

Oleh:

Ismartini, Pudji ; Sunaryo, Sony ; Setyawan

Jenis: Article from Journal - ilmiah nasional - terakreditasi DIKTI
Dalam koleksi: IPTEK: The Journal for Technology and Science vol. 21 no. 3 (Aug. 2010), page 118-123.
Topik: Partial Least Square Regression; Multicollinearity; Interval Estimator; Jackknife
Fulltext: The Jackknife Interval Estimation of Parametersin Partial Least Squares Regression Modelfor Poverty Data Analy.pdf (99.65KB)

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Perpustakaan Pusat (Semanggi) Nomor Panggil: MM48 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

One of 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 Square 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.

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