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Goodness of Fit for Discrete Random Variables Using the Conditional Density

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Abstract

In this paper we find a new test of goodness of fit in the case of discrete random variables. The main advantage of the methodology proposed in this paper relies on the fact that given the sample, we can control the probability of the type I error, that is α, and then find the exact value of the probability of the type II error, β, associated, in some cases. The results are not asymptotic, but exact. Also a conditional test for two alternatives is obtained. We also include some simulations in order to check the power of the procedures.

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Authors and Affiliations

  1. Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, UNAM, México, D.F., Mexico

    José M. González-Barrios, Federico O’Reilly & Raúl Rueda

Authors
  1. José M. González-Barrios
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  2. Federico O’Reilly
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  3. Raúl Rueda
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Correspondence to José M. González-Barrios.

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Mathematics Subject Classification (2000) Primary 62G10 · 62B05 · Secondary 62E10

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González-Barrios, J.M., O’Reilly, F. & Rueda, R. Goodness of Fit for Discrete Random Variables Using the Conditional Density. Metrika 64, 77–94 (2006). https://doi.org/10.1007/s00184-006-0035-1

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  • DOI: https://doi.org/10.1007/s00184-006-0035-1

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