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Random Variable Techniques

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Multivariate Calculation

Part of the book series: Springer Series in Statistics ((SSS))

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Abstract

In some parts of statistical inference it is customary to speak entirely in random variable terms, as in the analysis of variance. One considers his job finished when he writes the ratio of two independently distributed chi-square random variables, the denominator a central chi-square. There are a number of distribution problems in which by manipulation of the random variables involved one reduces the distribution problem to determination of the distribution of a relatively simple function of several independently distributed random variables. The theory of best linear unbiased estimation whereby a noncentral chi-square is obtained that is distributed independently of the sum of squares of error is in the meaning of this chapter a theory using random variable techniques. Another example that can at least partially be treated using random variable techniques is the example of Section 10.3, the multivariate beta density functions. See also Remark 5.7.3.

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© 1985 Springer-Verlag New York Inc.

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Farrell, R.H. (1985). Random Variable Techniques. In: Multivariate Calculation. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-8528-8_11

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  • DOI: https://doi.org/10.1007/978-1-4613-8528-8_11

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4613-8530-1

  • Online ISBN: 978-1-4613-8528-8

  • eBook Packages: Springer Book Archive

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