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Power maps in goodness-of-fit testing

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Abstract

For classical goodness-of-fit tests as well as for their modified versions in case of Type-II right censored data, results of a simulation study are presented, where the powers of the tests under consideration against beta alternatives are illustrated in informative, user-oriented plots that offer the possibility to directly choose the best test statistic in a concrete situation, when some prior belief about the alternative is available. The behavior of powers of respective statistical tests as functions of beta parameters is examined and discussed.

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References

  • Anderson TW, Darling DA (1952) Asymptotic theory of certain “goodness of fit” criteria based on stochastic process. Ann Math Stat 23:193–212

    Article  MathSciNet  MATH  Google Scholar 

  • Barr DR, Davidson T (1973) A Kolmogorov-Smirnov test for censored samples. Technometrics 15:739–757

    Article  MathSciNet  MATH  Google Scholar 

  • Best DJ, Rayner JCW (1985) Uniformity testing when alternatives have low order. Sankhyā Ser A 47:25–35

    MathSciNet  Google Scholar 

  • Birnbaum ZW, Lientz BP (1969) Tables of critical values of some Rényi type statistics for finite sample sizes. J Am Stat Assoc 64:870–877

    MathSciNet  Google Scholar 

  • Castro-Kuriss C, Kelmansky D, Leiva V, Martinez E (2009) A new goodness-of-fit test for censored data with an application in monitoring processes. Commun Stat Simul Comput 38:1161–1177

    Article  MathSciNet  MATH  Google Scholar 

  • Chen Z, Ye C (2009) An alternative test for uniformity. Int J Reliab Qual Saf Eng 16:343–356

    Article  Google Scholar 

  • Clemons TE (2001) Erratum to “A nonparametric measure of the overlapping coefficient”. Comput Stat Data Anal 36:243

    Google Scholar 

  • Clemons TE, Bradley EL (2000) A nonparametric measure of the overlapping coefficient. Comput Stat Data Anal 34:51–61

    Article  Google Scholar 

  • D’Agostino RB, Stephens MA (1986) Goodness-of-fit-techniques. Marcel Dekker, New York

    MATH  Google Scholar 

  • Durbin J (1968) The probability that the sample distribution function lies between two parallel straight lines. Ann Math Stat 39:398–411

    Article  MathSciNet  MATH  Google Scholar 

  • Durbin J (1971) Boundary-crossing probability for the Brownian motion and Poisson process and techniques for computing the power of the Kolmogorov-Smirnov test. J Appl Prob 8:431–453

    Article  MathSciNet  MATH  Google Scholar 

  • Durbin J, Knott M (1972) Components of Cramér-von Mises statistics I. J R Stat Soc Ser B 34:290–307

    MathSciNet  MATH  Google Scholar 

  • Durbin J, Knott M, Taylor CC (1975) Components of Cramér-von Mises statistics II. J R Stat Soc Ser B 37:216–237

    MathSciNet  MATH  Google Scholar 

  • Fielitz BD, Myers BL (1975) Estimation of parameters in the beta distribution. Decis Sci 6:1–13

    Article  Google Scholar 

  • Ghorai JK (1991) Cramér-von Mises statistic for testing goodness of fit under the proportional hazard model. Commun Stat Theory Meth 20:1107–1126

    Article  MathSciNet  MATH  Google Scholar 

  • Glen AG, Leemis LM, Barr DR (2001) Order statistics in goodness-of-fit testing. IEEE Trans Reliab 50:209–213

    Article  Google Scholar 

  • Gnanadesikan R, Pinkham RS, Hughes LP (1967) Maximum likelihood estimation of the parameters of the beta distribution from smallest order statistics. Technometrics 9:607–620

    Article  MathSciNet  MATH  Google Scholar 

  • Goegebeur Y, Guillou A (2010) Goodness-of-fit testing for Weibull-type behavior. J Stat Plann Inference 140:1417–1436

    Article  MathSciNet  MATH  Google Scholar 

  • Henze N, Meintanis SG (2005) Recent and classical tests for exponentiality: a partial review with comparisons. Metrika 61:29–45

    Google Scholar 

  • Johnson NL, Kotz S, Balakrishnan N (1995) Continuous univariate distributions. Wiley, New York

    MATH  Google Scholar 

  • Kolmogorov AN (1933) Sulla determinazione empirica di una legge di distribuzione. Giorna Ist Attuari 4:83–91

    MATH  Google Scholar 

  • LaRiccia VN (1986) Asymptotically chi-squared distributed tests of normality for type II censored samples. J Am Stat Assoc 81:1026–1031

    Article  MathSciNet  MATH  Google Scholar 

  • Lau HS, Lau AHL (1991) Effective procedures for estimating beta distribution’s parameters and their confidence intervals. J Stati Comput Simul 38:139–150

    Article  Google Scholar 

  • Ledwina T (1994) Data-driven version of Neyman’s smooth test of fit. J Am Stat Assoc 89:1000–1005

    Article  MathSciNet  MATH  Google Scholar 

  • Lim J, Park S (2007) Censored Kullback-Leibler information and goodness-of-fit test with type II censored data. J Appl Stat 34:1051–1064

    Article  MathSciNet  Google Scholar 

  • Lin CT, Huang YL, Balakrishnan N (2008) A new method for goodness-of-fit testing based on type-II right censored samples. IEEE Trans Reliab 57:633–642

    Article  Google Scholar 

  • Lurie D, Hartley HO, Stroud MR (1974) A goodness of fit test for censored data. Commun Stat 3:745–753

    MathSciNet  MATH  Google Scholar 

  • Marhuenda Y, Morales D, Pardo M (2005) A comparison of uniformity tests. Statistics 39:315–328

    Article  MathSciNet  MATH  Google Scholar 

  • Mehrotra KG (1982) On goodness of fit tests based on spacings for Type II censored samples. Commun Stat Theor Meth 11:869–878

    Article  MathSciNet  MATH  Google Scholar 

  • Meintanis SG (2008) A new approach of goodness-of-fit testing for exponentiated laws applied to the generalized Rayleigh distribution. Comput Stat Data Anal 52:2496–2503

    Article  MathSciNet  MATH  Google Scholar 

  • Meintanis SG (2009) Goodness-of-fit tests and minimum distance estimation via optimal transformation to uniformity. J Stat Plann Inference 139:100–108

    Article  MathSciNet  MATH  Google Scholar 

  • Meintanis SG, Bassiakos Y (2007) Data-transformation and test of fit for the generalized Pareto Hypothesis. Commun Stat Theory Meth 36:833–849

    Article  MathSciNet  MATH  Google Scholar 

  • Michael JR, Schucany WR (1979) A new approach to testing goodness of fit for censored samples. Technometrics 21:435–441

    Google Scholar 

  • Mihalko DP, Moore DS (1980) Chi-square tests of fit for Type II censored data. Ann Stat 8:625–644

    Article  MathSciNet  MATH  Google Scholar 

  • Milbrodt H, Strasser H (1990) On the asymptotic power of the two-sided Kolmogorov-Smirnov test. J Stat Plan Inference 26:1–23

    Article  MathSciNet  MATH  Google Scholar 

  • Miller FL, Quesenberry CP (1979) Power studies of some tests for uniformity, II. Commun Stat Simul Comput 8:271–290

    Article  Google Scholar 

  • Neuhaus G (1976) Asymptotic power properties of the Cramér-von Mises test under contiguous alternatives. J Multivar Anal 6:95–110

    Article  MathSciNet  MATH  Google Scholar 

  • Neyman J (1937) ’Smooth test’ for goodness of fit. Skand Aktuarietidskr 20:150–199

    Google Scholar 

  • Nguyen TT (2004) Maximum likelihood estimators of the parameters in a beta distribution. In: Gupta AK, Nadarajah S (eds) Handbook of beta distribution and its applications. Dekker, New York, pp 229–235

    Google Scholar 

  • O’Reilly FJ, Stephens MA (1988) Transforming censored samples for testing fit. Technometrics 30:79–86

    Article  MathSciNet  MATH  Google Scholar 

  • Pettitt AN, Stephens MA (1976) Modified Cramér-von Mises statistics for censored data. Biometrika 63:291–298

    MathSciNet  MATH  Google Scholar 

  • Quesenberry CP, Miller FL (1977) Power studies of some tests for uniformity. J Stat Comput Simul 5:169–191

    Article  MATH  Google Scholar 

  • Rényi A (1953) On the theory of order statistics. Acta Math Hungarica 4:191–231

    Article  MATH  Google Scholar 

  • Saldana-Zepeda DP, Vaquera-Huerta H, Arnold BC (2010) A goodness-of-fit test for the Pareto distribution in the presence of Type II censoring, based on the cumulative hazard function. Comput Stat Data Anal 54:833–842

    Article  MathSciNet  MATH  Google Scholar 

  • Smith RM, Bain LJ (1976) Correlation type goodness-of-fit statistics with censored sampling. Commun Stat 5:119–132

    Article  MathSciNet  Google Scholar 

  • Steele M, Chaseling J (2006) Powers of discrete goodness-of-fit test statistics for a uniform null against a selection of alternative distributions. Commun Stat Simul Comput 35:1067–1075

    Article  MathSciNet  MATH  Google Scholar 

  • Stephens MA (1974) Components of goodness-of-fit statistics. Ann Inst Henri Poincaré 10:37–54

    MathSciNet  MATH  Google Scholar 

  • Stephens MA (1974) EDF statistics for goodness of fit and some comparisons. J Am Stat Assoc 69:730–737

    Article  Google Scholar 

  • Stone CJ, Hansen MH, Kooperberg C, Truong YK (1997) Polynomial splines and their tensor products in extended linear modeling. Ann Stat 25:1371–1470

    Article  MathSciNet  MATH  Google Scholar 

  • Sürücü B (2008) A power comparison and simulation study of goodness-of-fit tests. Comput Math Appl 56:1617–1625

    Article  MathSciNet  MATH  Google Scholar 

  • Tiku ML (1980) Goodness of fit statistics based on the spacings of complete or censored samples. Aust J Stat 22:260–275

    Article  MathSciNet  MATH  Google Scholar 

  • Watson GS (1961) Goodness-of-fit tests on a circle. Biometrika 48:109–114

    MathSciNet  MATH  Google Scholar 

  • Xu X, Ding X, Zhao S (2009) New goodness-of-fit tests based on fiducial empirical distribution function. Comput Stat Data Anal 53:1132–1141

    Article  MathSciNet  MATH  Google Scholar 

  • Zhao J, Xu X, Ding X (2009) Some new goodness-of-fit tests based on stochastic sample quantiles. Commun Stat Simul Comput 38:571–589

    Article  MathSciNet  MATH  Google Scholar 

  • Zhao J, Xu X, Ding X (2010) New goodness of fit tests based on stochastic EDF. Commun Stat Theory Meth 39:1075–1094

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgments

The authors are grateful to Christian Baart for implementing the Java applet described in Sect. 2, and to the reviewers for their helpful comments.

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Correspondence to T. Fischer.

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Fischer, T., Kamps, U. Power maps in goodness-of-fit testing. Comput Stat 28, 1365–1382 (2013). https://doi.org/10.1007/s00180-012-0361-x

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