Abstract
Typically the literature has advocated the use of the dominant right eigenvector and an associated consistency ratio “C.R.” We give reasons why the geometric mean (GM) (also known as the LLSM or logarithmic least-squares method) may be preferable as an estimator of the unknown underlying scale u. We also develop an index of consistency and related rules to judge the consistency of a matrix when using the GM as an estimator. The rules for the index of consistency are closely related to the commonly used rule that the C.R. should be <0.1.
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