The Rayleigh distribution is widely used to model events that occur in different fields such as medicine and natural sciences. In this article, we suggest some test statistics for examining the Rayleigh goodness of fit based on the empirical distribution function. Critical points and power of the tests are obtained by Monte Carlo simulation. We show that the proposed tests have a good performance against different alternatives and therefore these tests can be confidently used in practice. Finally, the proposed tests are illustrated by real data examples.
V. Ahrari, S. Baratpour, A. Habibirad, and V. Fakoor, Goodness of fit tests for Rayleigh distribution based on quantiles, Comm. Statist. Simulation Comput., 51 (2022), pp. 341–357.
R. Alizadeh Noughabi, H. Alizadeh Noughabi, and A. Ebrahimi Moghaddam Behabadi, An entropy test for the Rayleigh distribution and power comparison, J. Stat. Comput. Simul., 84 (2014), pp. 151–158.
T. W. Anderson and D. A. Darling, A test of goodness of fit, J. Amer. Statist. Assoc., 49 (1954), pp. 765– 769.
S. Baratpour and F. a. Khodadadi, A cumulative residual entropy characterization of the Rayleigh distribution and related goodness-of-fit test, J. Statist. Res. Iran, 9 (2013), pp. 115–131.
S. Baratpour and A. H. Rad, Testing goodness-of-fit for exponential distribution based on cumulative residual entropy, Comm. Statist. Theory Methods, 41 (2012), pp. 1387–1396.
S. K. Bhattacharya and K. T. Ravinder, Bayesian survival analysis based on the Rayleigh model, Trabajos de Estad´ıstica, 5 (1990), pp. 81–92.
C. Caroni, The correct “ball bearings” data, Lifetime Data Anal., 8 (2002), pp. 395–399.
Z. Chen, A new two-parameter lifetime distribution with bathtub shape or increasing failure rate function, Statistics & Probability Letters, 49 (2000), pp. 155–161.
Y. Chung, Estimation of scale parameter from Rayleigh distribution under entropy loss, J. Appl. Math. Comput., 2 (1995), pp. 33–40.
R. B. D’Agostino and M. A. Stephens, Goodness-of-fit techniques, Marcel Dekker, Inc., USA, 1986.
S. Dey and S. Maiti, Bayesian estimation of the parameter of Rayleigh distribution under the extended Jeffrey’s prior, Electron. J. Appl. Stat. Anal., 5 (2012), pp. 44–59.
B. S. Dhillon, Life distributions, IEEE Transactions on Reliability, R-30 (1981), pp. 457–460.
D. D. Dyer and C. W. Whisenand, Best linear unbiased estimator of the parameter of the Rayleigh distribution, IEEE Transactions on Reliability, R-22 (1973), pp. 229–231.
A. J. Fernandez´ , Bayesian estimation and prediction based on Rayleigh sample quantiles, Quality & Quantity, 44 (2010), pp. 1239–1248.
D. Hinkley, On quick choice of power transformation, Journal of the Royal Statistical Society. Series C (Applied Statistics), 26 (1977), pp. 67–69.
S. M. A. Jahanshahi, A. H. Rad, and V. Fakoor, A goodness-of-fit test for Rayleigh distribution based on hellinger distance, Annals of Data Science, 3 (2016), pp. 401–411.
S. M. A. Jahanshahi, A. H. Rad, and V. Fakoor, Some new goodness-of-fit tests for Rayleigh distribution, Pak. J. Stat. Oper. Res., (2020), pp. 305–315.
N. L. Johnson, S. Kotz, and N. Balakrishnan, Continuous Univariate Distributions, Volume 1, Wiley Series in Probability and Statistics, John Wiley & Sons, Nashville, TN, 2 ed., 1994.
A. Kohansal and S. Rezakhah, Inference of R = P(Y < X) for two-parameter Rayleigh distribution based on progressively censored samples, Statistics, 53 (2019), pp. 81–100.
A. Kolmogoroff, Sulla determinazione empirica di una legge di distribuzione., G. Ist. Ital. Attuari, 4 (1933), pp. 83–91.
N. H. Kuiper, Tests concerning random points on a circle, Nederl. Akad. Wet., Proc., Ser. A, 63 (1960), pp. 38–47.
H. Liao and W. Gui, Statistical inference of the Rayleigh distribution based on progressively type-II censored competing risks data, Symmetry, 11 (2019), p. 898.
S. Liebenberg and J. Allison, A review of goodness-of-fit tests for the Rayleigh distribution, Austrian Journal of Statistics, 52 (2023), pp. 1–22.
A. Pak, G. A. Parham, and M. Saraj, Inference for the Rayleigh distribution based on progressive type-II fuzzy censored data, J. Mod. Appl. Stat. Methods, 13 (2014), pp. 287–304.
L. Rayleigh, On the resultant of a large number of vibrations of the same pitch and of arbitrary phase, Phil. Mag. (5), 10 (1880), pp. 73–78.
J. Ren and W. Gui, Goodness-of-fit test for Rayleigh distribution based on progressively type-II censored sample, Commun. Stat., Theory Methods, 50 (2021), pp. 3851–3874.
M. Safavinejad, S. Jomhoori, and H. A. Noughabi, A density-based empirical likelihood ratio goodnessof-fit test for the Rayleigh distribution and power comparison, J. Stat. Comput. Simulation, 85 (2015), pp. 3322– 3334.
M. M. Siddiqui, Some problems connected with Rayleigh distributions, J. Res. Natl. Bur. Stand., Sect. D, 66 (1962), pp. 167–174.
M. M. Siddisqui, Statistical inference for Rayleigh distributions, J. Res. Natl. Bur. Stand., Sect. D, 68 (1964), pp. 1005–1010.
H. Torabi, N. H. Montazeri, and A. Grane´, A test for normality based on the empirical distribution function, SORT, 40 (2016), pp. 55–88.
, A wide review on exponentiality tests and two competitive proposals with application on reliability, J. Stat. Comput. Simulation, 88 (2018), pp. 108–139.
K. M. Vaisakh, T. Xavier, and E. P. Sreedevi, Goodness of fit test for Rayleigh distribution with censored observations, J. Korean Statist. Soc., 52 (2023), pp. 794–815.
R. von Mises, Vorlesungen aus dem Gebiete der angewandten Mathematik. Bd. 1. Wahrscheinlichkeitsrechnung und ihre Anwendung in der Statistik und theoretischen Physik. Leipzig u. Wien: Franz Deuticke. X, 574 S. u. 90 Abb. (1931)., 1931.
G. S. Watson, Goodness-of-fit tests on a circle, Biometrika, 48 (1961), pp. 109–114.
E. Zamanzade and M. Mahdizadeh, Goodness of fit tests for Rayleigh distribution based on Phi-divergence, Rev. Colomb. Estad., 40 (2017), pp. 279–290.
Alizadeh Noughabi, H. and Shafaei Noughabi, M. (2025). Power study of goodness of fit tests for the Rayleigh distribution based on the empirical distribution function with application to real data. AUT Journal of Mathematics and Computing, 6(3), 205-215. doi: 10.22060/ajmc.2024.22768.1193
MLA
Alizadeh Noughabi, H. , and Shafaei Noughabi, M. . "Power study of goodness of fit tests for the Rayleigh distribution based on the empirical distribution function with application to real data", AUT Journal of Mathematics and Computing, 6, 3, 2025, 205-215. doi: 10.22060/ajmc.2024.22768.1193
HARVARD
Alizadeh Noughabi, H., Shafaei Noughabi, M. (2025). 'Power study of goodness of fit tests for the Rayleigh distribution based on the empirical distribution function with application to real data', AUT Journal of Mathematics and Computing, 6(3), pp. 205-215. doi: 10.22060/ajmc.2024.22768.1193
CHICAGO
H. Alizadeh Noughabi and M. Shafaei Noughabi, "Power study of goodness of fit tests for the Rayleigh distribution based on the empirical distribution function with application to real data," AUT Journal of Mathematics and Computing, 6 3 (2025): 205-215, doi: 10.22060/ajmc.2024.22768.1193
VANCOUVER
Alizadeh Noughabi, H., Shafaei Noughabi, M. Power study of goodness of fit tests for the Rayleigh distribution based on the empirical distribution function with application to real data. AUT Journal of Mathematics and Computing, 2025; 6(3): 205-215. doi: 10.22060/ajmc.2024.22768.1193