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A multivariate Kolmogorov-Smirnov test of goodness of fit

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  • Justel, Ana
  • Peña, Daniel
  • Zamar, Rubén

Abstract

This paper presents a distribution-free multivariate Kolmogorov-Smirnov goodness-of-fit test. The test uses a statistic which is built using Rosenblatt's transformation and an algorithm is developed to compute it in the bivariate case. An approximate test, that can be easily computed in any dimension, is also presented. The power of these multivariate tests is studied in a simulation study.

Suggested Citation

  • Justel, Ana & Peña, Daniel & Zamar, Rubén, 1997. "A multivariate Kolmogorov-Smirnov test of goodness of fit," Statistics & Probability Letters, Elsevier, vol. 35(3), pages 251-259, October.
    • Handle: RePEc:eee:stapro:v:35:y:1997:i:3:p:251-259
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    References listed on IDEAS

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    1. N. J. H. Small, 1980. "Marginal Skewness and Kurtosis in Testing Multivariate Normality," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(1), pages 85-87, March.
    2. J. P. Royston, 1983. "Some Techniques for Assessing Multivarate Normality Based on the Shapiro‐Wilk W," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 32(2), pages 121-133, June.
    3. Einmahl, J. H.J. & Mason, D.M., 1992. "Generalized quantile processes," Other publications TiSEM b2a76bac-045d-457f-869f-d, Tilburg University, School of Economics and Management.
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