THE SMALL SAMPLE PROPERTIES OF THE PRINCIPAL COMPONENTS ESTIMATOR FOR REGRESSION COEFFICIENTS
ABSTRACT Under the mean square error matrix (MSEM) criterion and Pitman closeness (PC) criterion, the principal components estimator (PRCE) is compared with the least square estimator (LSE) and the superiority of PRCE over LSE is achieved respectively. Finally, we examine the superiority of PRCE predictor over the LSE predictor based on these two criteria.