An approximate method for generating asymmetric random variables
Communications of the ACM
An approximate method for generating symmetric random variables
Communications of the ACM
The Role of Statistics in IS/IT: Practical Gains from Mined Data
Information Systems Frontiers
Computational Statistics & Data Analysis
The Mathematica Book
Characterizing the generalized lambda distribution by L-moments
Computational Statistics & Data Analysis
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A sample version of the power-divergence measures of Cressie and Read is proposed for the influence analysis in the logistic regression model. Influence measures are obtained by quantifying the deviation between the sample distribution of an estimate obtained with all the observations and the sample distribution of the same estimate obtained without any observation. In particular, this approach is applied to three estimates of the model: the MLE of regression coefficients vector, the probabilities vector and the linear predictor of a future case. Some examples are considered to clarify the usefulness of the introduced diagnostics.