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    Outlier detection and parameter estimation in multivariate multiple regression (MMR) 

    Paweena Tangjuang; Pachitjanut Siripanich (National Institute of Development Administration, 2013)

    Outlier detection in Y-direction for multivariate multiple regression data is interesting since there are correlations between the dependent variables which is one cause of difficulty in detecting multivariate outliers, furthermore, the presence of the outliers may change the values of the estimators arbitrarily. Having an alternative method that can detect those outliers is necessary so that reliable results can be obtained. The multivariate outlier detection methods have been developed by many researchers. But in this study, Mahalanobis ...
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    Tests for gamma distribution based on its independence property 

    Bandhita Plubin; Pachitjanut Siripanich (National Institute of Development Administration, 2015)

    There are two test statistics proposed in this study in order to test whether data come from a gamma distribution. Both of the proposed test statistics are developed from a modified Kendall coefficient based on the independence property of a gamma distribution. The first one is asymptotically distributed as standard normal and the limit distribution function of the second one was improved using an Edgeworth expansion and the Jackknife method. They are invariant to scale parameters and perform substantially better than existing tests in terms of ...