Recognizing distributions rather than goodness-of-fit testing

References

• AbouRizk, S. M., D. W. Halpin, and J. R. Wilson. 1994. Fitting beta distributions based on sample data. Journal of Construction Engineering and Management 120 (2):288–305. doi:10.1061/(ASCE)0733-9364(1994)120:2(288).
   Web of Science ®Google Scholar
• Aherne, F. J., N. A. Thacker, and P. I. Rockett. 1998. The Bhattacharyya metric as an absolute similarity measure for frequency coded data. Kybernetika 34 (4):363–68.
   Web of Science ®Google Scholar
• Ahmad, F., and R. A. Khan. 2015. A power comparison of various normality tests. Pakistan Journal of Statistics and Operation Research 11 (3):331–45. doi:10.18187/pjsor.v11i3.845.
   Web of Science ®Google Scholar
• Alizadeh Noughabi, H., and N. R. Arghami. 2011. Monte Carlo comparison of seven normality tests. Journal of Statistical Computation and Simulation 81 (8):965–72. doi:10.1080/00949650903580047.
   Web of Science ®Google Scholar
• Anderson, T. W., and D. A. Darling. 1952. Asymptotic theory of certain "goodness-of-fit" criteria based on stochastic processes. The Annals of Mathematical Statistics 23 (2):193–212. doi:10.1214/aoms/1177729437.
   Google Scholar
• Ball, G. H., and D. J. Hall. 1965. ISODATA, a novel method of data analysis and pattern classification. California: Stanford Research Institute Menlo Park.
   Google Scholar
• Cha, S. H. 2007. Comprehensive survey on distance/similarity measures between probability density functions. City 1 (2):1.
   Google Scholar
• Cramér, H. 1928. On the composition of elementary errors. Scandinavian Actuarial Journal 1928 (1):13–74. doi:10.1080/03461238.1928.10416862.
   Google Scholar
• Cruz-Medina, I. R. 2001. Almost nonparametric and nonparametric estimation in mixture models. PhD diss., Pennsylvania State University, University Park.
   Google Scholar
• Denby, L., and C. Mallows. 2009. Variations on the histogram. Journal of Computational and Graphical Statistics 18 (1):21–31. doi:10.1198/jcgs.2009.0002.
   Web of Science ®Google Scholar
• Hassan, M. Y., and R. H. Hijazi. 2010. A bimodal exponential power distribution. Pakistan Journal of Statistics 26 (2):379–96.
   Web of Science ®Google Scholar
• Kolmogorov, A. 1933. Sulla determinazione empirica di unalegge di distributione. Giornale dell’ Istituto Italiano degli Attuari 4:83–91.
   Google Scholar
• Lemonte, A. J. 2013. A new extension of the Birnbaum–Saunders distribution. Brazilian Journal of Probability and Statistics 27 (2):133–49. doi:10.1214/11-BJPS160.
   Web of Science ®Google Scholar
• Lilliefors, H. W. 1967. On the Kolmogorov-Smirnov test for normality with mean and variance unknown. Journal of the American Statistical Association 62 (318):399–402. doi:10.1080/01621459.1967.10482916.
   Web of Science ®Google Scholar
• Matusita, K. 1955. Decision rules based on distance for problems of fit, two samples and estimation. The Annals of Mathematical Statistics 26 (4):631–41. doi:10.1214/aoms/1177728422.
   Google Scholar
• Nichols, M. D., and W. J. Padgett. 2006. A bootstrap control chart for Weibull percentiles. Quality and Reliability Engineering International 22 (2):141–51. doi:10.1002/qre.691.
   Web of Science ®Google Scholar
• Razali, N. M., and Y. B. Wah. 2011. Power comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling tests. Journal of Statistical Modeling and Analytics 2 (1):21–33.
   Google Scholar
• Romao, X., R. Delgado, and A. Costa. 2010. An empirical power comparison of univariate goodness-of-fit tests of normality. Journal of Statistical Computation and Simulation 80 (5):545–91. doi:10.1080/00949650902740824.
   Web of Science ®Google Scholar
• Shapiro, S. S., and M. B. Wilk. 1965. An analysis of variance test for normality. Biometrika 52 (3-4):591–611. doi:10.2307/2333709.
   Web of Science ®Google Scholar
• Smirnov, N. 1948. Table for estimating the goodness of fit of empirical distributions. The Annals of Mathematical Statistics 19 (2):279–81. doi:10.1214/aoms/1177730256.
   Google Scholar
• Sulewski, P. 2019. Modified Lilliefors goodness-of-fit test for normality. Communications in Statistics - Simulation and Computation. Advance online publication. doi:10.1080/03610918.2019.1664580.
   Web of Science ®Google Scholar
• Sulewski, P. 2020. Equal-bin-width histogram versus equal-bin-count histogram. Journal of Applied Statistics. Advance online publication. doi:10.1080/02664763.2020.1784853.
   PubMed Web of Science ®Google Scholar
• Torabi, H., N. H. Montazeri, and A. Grané. 2016. A test of normality based on the empirical distribution function. SORT 40 (1):55–88.
   Web of Science ®Google Scholar
• Urzúa, C. M. 1996. On the correct use of omnibus tests for normality. Economics Letters 53 (3):247–51.
   Web of Science ®Google Scholar
• Yap, B. W., and C. H. Sim. 2011. Comparisons of various types of normality tests. Journal of Statistical Computation and Simulation 81 (12):2141–55. doi:10.1080/00949655.2010.520163.
   Web of Science ®Google Scholar
• Yazici, B., and S. A. Yolacan. 2007. Comparison of various tests of normality. Journal of Statistical Computation and Simulation 77 (2):175–83. doi:10.1080/10629360600678310.
   Web of Science ®Google Scholar