| Resumo: | F-tests may not be used for all relevant hypothesis, even in rather simple models, which led to the introduction of generalized F-tests. The statistics of these tests are quotients of linear combinations of independent chi-squares, which may be non-central. When the observations are collected under non-standardized conditions, the non-centrality parameters may be random. The generalized F distributions are given by infinite sums. In this study, we show that there is an excellent control of the truncations errors for those sums. The case in which the non-centrality parameters have Gamma distributions is singled out.
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