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Research Centre
Data - Algorithms - Decision Making
Data - Algorithms - Decision Making
Established in 2005 under support of MŠMT ČR (project 1M0572)
Publications
Goodness-of-Fit Disparity Statistics Obtained by Hypothetical and Empirical Quantizations
Typ:
Research report
Name of edition:
Research Report
Article number:
2292
Serie:
Praha
Year:
2010
Keywords:
power divergences, goodness-of-fit, asymptotic normality,
Anotation:
Goodness-of-fit disparity statistics are defined as appropriately scaled phi-disparities or phi-divergences of quantized hypothetical and empirical distributions. It is shown that the classical Pearson-type statistics are obtained if we quantize by means of hypothetical percentiles, and that new spacings-based disparity statistics are obtained if we quantize by means of empirical percentiles.