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Abstract

We hope to arrive at powerful tests using test statistics of the quadratic ratio type (2.1) with significance points that can be tabulated. For this purpose, we developed the BLUF estimator w of Ju; see (3.2). The estimator depends on the following matrices: the n × p matrix J, the p × p matrix Q, the p × p matrix Ω = KK ′, the n × n matrix Г, the n × k matrix X, and the n-element vector y. Both X and y are specified by observation and it is assumed that y ~n(, σ2 Г), where Г = Г 0 under the null hypothesis ℋ 0 . Hence, Г in (3.2) is specified by ℋ 0 . One is free to choose J and Q. The only practical specifications we know are J = I(n) or J is an n × (n−k) submatrix of I(n), like J in the BLUS vectors, and Q = I or Q = Г−1. In this chapter we take J = I, so that p = n. Because most current tests have Г = I as the null hypothesis, the most important specifications for practical application would seem to be Г= Q = J = I(n).

Keywords

Scalar Multiplication Cipal Component Selection Device Economic Time Series Regression Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© H. E. Stenfert Kroese B.V. 1978

Authors and Affiliations

  • C. Dubbelman
    • 1
  1. 1.Econometric InstituteErasmus University RotterdamNetherlands

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