Landaburu Jiménez, María Elena and Morales González, Domingo and Pardo Llorente, Leandro (2005) Divergence-based estimation and testing with misclassified data. Statistical Papers, 46 (3). pp. 397-409. ISSN 0932-5026
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The well-known chi-squared goodness-of-fit test for a multinomial distribution is generally biased when the observations are subject to misclassification. In Pardo and Zografos (2000) the problem was considered using a double sampling scheme and phi-divergence test statistics. A new problem appears if the null hypothesis is not simple because it is necessary to give estimators for the unknown parameters. In this paper the minimum phi-divergence estimators are considered and some of their properties are established. The proposed phi-divergence test statistics are obtained by calculating phi-divergences between probability density functions and by replacing parameters by their minimum phi-divergence estimators in the derived expressions. Asymptotic distributions of the new test statistics are also obtained. The testing procedure is illustrated with an example
|Uncontrolled Keywords:||Misclassification; Double sampling; Divergence estimators; Goodness-of-fit tests; Divergence statistics|
|Subjects:||Sciences > Statistics > Sampling (Statistics)|
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|Deposited On:||20 Sep 2012 09:05|
|Last Modified:||07 Feb 2014 09:29|
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