Goodness of fit tests via exponential series density estimation

TY - JOUR

T1 - Goodness of fit tests via exponential series density estimation

AU - Marsh, P.

PY - 2007/2

Y1 - 2007/2

N2 - 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.

AB - 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.

KW - goodness of fit

KW - exponential series density estimator

KW - ORTHOGONAL EXPANSIONS

KW - MODEL

KW - NORMALITY

KW - FAMILIES

U2 - 10.1016/j.csda.2006.08.021

DO - 10.1016/j.csda.2006.08.021

M3 - Article

SN - 0167-9473

VL - 51

SP - 2428

EP - 2441

JO - Computational Statistics & Data Analysis

JF - Computational Statistics & Data Analysis

IS - 5

ER -