Obenchain (1977) claimed that ridge techniques with nonstochastic of biased factors don't generally yield "new" normal theory statistical inference than that used in least squares technique, and that the t and F statistics are identical under both techniques. Theorems (1)-(3), in this paper, prove that this is true when using the unbasid ordinary least squares estimator S2 of σ2 Moreover, a counter example is introduced to show that the normal theory doesn't apply when using the ridge regression estimator Sr2 of σ2 instead of using the least squares estimator S2.
Azzam, A. (1996). Inference in Linear Models with Nonstochastic Biased Factors. The Egyptian Statistical Journal, 40(2), 172-181. doi: 10.21608/esju.1996.314788
MLA
Abdul-Mordy H. Azzam. "Inference in Linear Models with Nonstochastic Biased Factors", The Egyptian Statistical Journal, 40, 2, 1996, 172-181. doi: 10.21608/esju.1996.314788
HARVARD
Azzam, A. (1996). 'Inference in Linear Models with Nonstochastic Biased Factors', The Egyptian Statistical Journal, 40(2), pp. 172-181. doi: 10.21608/esju.1996.314788
VANCOUVER
Azzam, A. Inference in Linear Models with Nonstochastic Biased Factors. The Egyptian Statistical Journal, 1996; 40(2): 172-181. doi: 10.21608/esju.1996.314788
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