In this chapter we take up the problems occasioned by the failure of the rank condition (for the matrix of explanatory variables). This problem arises as a matter of course in analysis of variance (or covariance) models where some of the variables are classificatory. In this case, we are led to the construction of “dummy” variables representing the classificatory schemes. Since all such classificatory schemes are exhaustive, it is not surprising that the “dummy” variables are linearly dependent and, thus, the rank condition for the data matrix fails.
KeywordsUnbiased Estimator Rank Condition Ridge Regression Good Linear Unbiased Estimator Payout Ratio
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