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72.
We define a new family of influence measures based on the divergence measures, in the multivariate general linear model. Influence measures are obtained by quantifying the divergence between the sample distribution of an estimate obtained with all the observations and the sample distribution of the same estimate obtained without any observation. This approach is applied to best linear unbiased estimates of estimable functions. Therefore, these diagnostics can be applied to every statistical multivariate technique that can be formulated like this kind of model. Some examples are considered to clarify the applicability of the introduced diagnostics. 相似文献
73.
In this paper we introduce and study two new families of statistics for the problem of testing linear combinations of the parameters in logistic regression models. These families are based on the phi-divergence measures. One of them includes the classical likelihood ratio statistic and the other the classical Pearson's statistic for this problem. It is interesting to note that the vector of unknown parameters, in the two new families of phi-divergence statistics considered in this paper, is estimated using the minimum phi-divergence estimator instead of the maximum likelihood estimator. Minimum phi-divergence estimators are a natural extension of the maximum likelihood estimator. 相似文献
74.
Arjun K. Gupta Solomon W. Harrar Leandro Pardo 《Statistical Methods and Applications》2007,16(2):245-261
This paper deals with testing equality of variances of observations in the different treatment groups assuming treatment effects
are fixed. We study the distribution of a test statistic which is known to perform comparably well with other statistics for
the same purpose under normality. The statistic we consider is based on Shannon’s entropy for a distribution function. We
will derive the asymptotic expansion for the distribution of the test statistic based on Shannon’s entropy under nonnormality
and numerically examine its performance in comparison with the modified likelihood ratio criteria for normal and some nonnormal
populations.
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