Improved Shrinkage Estimation of Squared Multiple Correlation Coefficient and Squared Cross-Validity Coefficient  

Oleh:

Shieh, Gwowen

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Organizational Research Methods vol. 11 no. 2 (Apr. 2008), page 387-407.
Topik: Bias; Maximum Likelihood Estimator; Mean Square Error; Multiple Linear Regression; Shrinkage Estimator
Fulltext: 387.pdf (259.71KB)

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Perpustakaan Pusat (Semanggi) Nomor Panggil: OO3.9 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

The sample squared multiple correlation coefficient is widely used for describing the usefulness of a multiple linear regression model in many areas of science. In this article, the author considers the problem of estimating the squared multiple correlation coefficient and the squared cross-validity coefficient under the assumption that the response and predictor variables have a joint multinormal distribution. Detailed numerical investigations are conducted to assess the exact bias and mean square error of the proposed modifications of established estimators. Notably, the positive-part Pratt estimator and the synthesis of Browne and positive-part Pratt estimators are recommended in the estimation of squared multiple correlation coefficient and squared cross-validity coefficient, respectively, for their overall advantages of incurring the least amount of statistical discrepancy and computational requirement.

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