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Journal of the American Statistical Association, 1967
Abstract This Paper defines a class of distribution free measures of goodness of fit; their exact distribution for small samples can be calculated by means of a computer. Two of them have the same asymptotic distribution as the Kolmogorov-Smirnov statistic.
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Abstract This Paper defines a class of distribution free measures of goodness of fit; their exact distribution for small samples can be calculated by means of a computer. Two of them have the same asymptotic distribution as the Kolmogorov-Smirnov statistic.
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1987
As before, let ξ1, ..., ξn be univariate independent random variables with the same continuous d.f. F Recall $${\text{D}}_{\text{n}} = \mathop {\sup }\limits_{\text{t}} |{\text{F}}_{\text{n}} \left( {\text{t}} \right) - {\text{F}}\left( {\text{t}} \right)| $$ , the Kolmogorov goodness of fit statistic.
Peter Gaenssler, Winfried Stute
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As before, let ξ1, ..., ξn be univariate independent random variables with the same continuous d.f. F Recall $${\text{D}}_{\text{n}} = \mathop {\sup }\limits_{\text{t}} |{\text{F}}_{\text{n}} \left( {\text{t}} \right) - {\text{F}}\left( {\text{t}} \right)| $$ , the Kolmogorov goodness of fit statistic.
Peter Gaenssler, Winfried Stute
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Length tests for goodnesss-of-fit
Biometrika, 1991Consider an i.i.d. sample X 1,..., X n with distribution function F, which throughout is assumed to be twice continuously differentiable with support [0,1] and strictly positive derivative on [0,1]. Denote by $$0={X_{0:n}}\leqslant {X_{1:n}}\leqslant\cdots\leqslant{X_{n:n}}\leqslant{X_{n+1:n}}=1$$ (1) the order statistics, and the spacings by
Reschenhofer, Erhard, Bomze, Immanuel
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1999
Goodness-of-fit tests for continuos distributions are generally handled by the Kolmogorov-Smirnov test which in its classical form requires that the distribution is completely specified. In practice this is seldom the case and one then resorts to estimating parameters from the data and then examining Kolmogorov-Smirnov “type” tests. The standard tables
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Goodness-of-fit tests for continuos distributions are generally handled by the Kolmogorov-Smirnov test which in its classical form requires that the distribution is completely specified. In practice this is seldom the case and one then resorts to estimating parameters from the data and then examining Kolmogorov-Smirnov “type” tests. The standard tables
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GOODNESS OF FIT FOR THE BINOMIAL DISTRIBUTION
Australian Journal of Statistics, 1997SummaryGoodness of fit testing for the binomial distribution can be carried out using Pearson's X2p statistic and its components. Applications of this technique are considered and compared with recently suggested empirical distribution function tests. Diagnostic use of components is discussed.
Best, D. J., Rayner, J. C. W.
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Goodness-of-Fit Tests on a Circle. II
Biometrika, 1961Abstract : A statistical analysis is made by use of the null hypothesis test for random samples which have been drawn from a population with the continuous distribution function F(x). It is useful for distributions on a circle since its value does not depend on the arbitrary point chosen to begin cumulating the probability density and the sample points.
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1996
Abstract Throughout the previous chapters, we have seen various aspects of the model building process. In Chapter 3, we generally assumed that the chosen family of models, 𝒫, was suitable, and studied how to rank the relative merits of different members of that family, whether different functional forms or simply different parameter ...
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Abstract Throughout the previous chapters, we have seen various aspects of the model building process. In Chapter 3, we generally assumed that the chosen family of models, 𝒫, was suitable, and studied how to rank the relative merits of different members of that family, whether different functional forms or simply different parameter ...
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Goodness of Fit and Related Inference Processes for Quantile Regression
Journal of the American Statistical Association, 1999Roger Koenker
exaly