Goodness of fit tests via exponential series density estimation

Research output: Contribution to journalArticlepeer-review



Publication details

JournalComputational Statistics & Data Analysis
DatePublished - Feb 2007
Issue number5
Number of pages13
Pages (from-to)2428-2441
Original languageEnglish


The properties of a new nonparametric goodness of fit test are explored. It is based on a likelihood ratio test, applied via a consistent series density estimator in the exponential family. The focus is on its computational and numerical properties. Specifically it is found that the choice of approximating basis is not crucial and that the choice of model dimension, through data-driven selection criteria, yields a feasible, parsimonious procedure. Numerical experiments show that the new tests have significantly more power than established tests, whether based upon the empirical distribution function, or alternate density estimators.

    Research areas

  • goodness of fit, exponential series density estimator, ORTHOGONAL EXPANSIONS, MODEL, NORMALITY, FAMILIES

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