Skip to main content

Quantile Functions

  • Chapter
  • First Online:
Quantile-Based Reliability Analysis

Abstract

A probability distribution can be specified either in terms of the distribution function or by the quantile function. This chapter addresses the problem of describing the various characteristics of a distribution through its quantile function. We give a brief summary of the important milestones in the development of this area of research. The definition and properties of the quantile function with examples are presented. In Table 1.1, quantile functions of various life distributions, representing different data situations, are included. Descriptive measures of the distributions such as location, dispersion and skewness are traditionally expressed in terms of the moments. The limitations of such measures are pointed out and some alternative quantile-based measures are discussed. Order statistics play an important role in statistical analysis. Distributions of order statistics in quantile forms, their properties and role in reliability analysis form the next topic in the chapter. There are many problems associated with the use of conventional moments in modelling and analysis. Exploring these, and as an alternative, the definition, properties and application of L-moments in describing a distribution are presented. Finally, the role of certain graphical representations like the Q-Q plot, box-plot and leaf-plot are shown to be useful tools for a preliminary analysis of the data.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    There are different choices for these plotting points and recently Balakrishnan et al. [52] discussed the determination of optimal plotting points by the use of Pitman closeness criterion.

References

  1. Abromowitz, M., Stegun, I.A.: Handbook of Mathematical Functions: Formulas, Graphs and Mathematical Tables. Applied Mathematics Series, vol. 55. National Bureau of Standards, Washington, DC (1964)

    Google Scholar 

  2. Adamidis, K., Loukas, S.: A lifetime distribution with decreasing failure rate. Stat. Probab. Lett. 39, 35–42 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  3. Arnold, B.C., Balakrishnan, N., Nagaraja, H.N.: A First Course in Order Statistics. Wiley, New York (1992)

    MATH  Google Scholar 

  4. Avinadav, T., Raz, T.: A new inverted hazard rate function. IEEE Trans. Reliab. 57, 32–40 (2008)

    Article  Google Scholar 

  5. Balakrishnan, N.: Order statistics from the half logistic distribution. J. Stat. Comput. Simulat. 20, 287–309 (1985)

    Article  Google Scholar 

  6. Balakrishnan, N. (ed.): Handbook of the Logistic Distribution. Marcel Dekker, New York (1992)

    MATH  Google Scholar 

  7. Balakrishnan, N., Aggarwala, R.: Relationships for moments of order statistics from the right-truncated generalized half logistic distribution. Ann. Inst. Stat. Math. 48, 519–534 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  8. Balakrishnan, N., Cohen, A.C.: Order Statistics and Inference: Estimation Methods. Academic, Boston (1991)

    MATH  Google Scholar 

  9. Balakrishnan, N., Davies, K., Keating, J.P., Mason, R.L.: Computation of optimal plotting points based on Pitman closeness with an application to goodness-of-fit for location-scale families. Comput. Stat. Data Anal. 56, 2637–2649 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  10. Balakrishnan, N., Kundu, D.: Hybrid censoring: Models, inferential results and applications (with discussions). Comput. Stat. Data Anal. 57, 166–209 (2013)

    Article  MathSciNet  Google Scholar 

  11. Balakrishnan, N., Rao, C.R.: Order Statistics: Theory and Methods. Handbook of Statistics, vol. 16. North-Holland, Amsterdam (1998)

    Google Scholar 

  12. Balakrishnan, N., Rao, C.R.: Order Statistics - Applications. Handbook of Statistics, vol. 17. North-Holland, Amsterdam (1998)

    Google Scholar 

  13. Balakrishnan, N., Sandhu, R.: Recurrence relations for single and product moments of order statistics from a generalized half logistic distribution, with applications to inference. J. Stat. Comput. Simulat. 52, 385–398 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  14. Balakrishnan, N., Wong, K.H.T.: Approximate MLEs for the location and scale parameters of the half-logistic distribution with Type-II right-censoring. IEEE Trans. Reliab. 40, 140–145 (1991)

    Article  MATH  Google Scholar 

  15. Balanda, K.P., MacGillivray, H.L.: Kurtosis: a critical review. Am. Stat. 42, 111–119 (1988)

    Google Scholar 

  16. Chen, G., Balakrishnan, N.: The infeasibility of probability weighted moments estimation of some generalized distributions. In: Balakrishnan, N. (ed.) Recent Advances in Life-Testing and Reliability, pp. 565–573. CRC Press, Boca Raton (1995)

    Google Scholar 

  17. Cohen, A.C.: Truncated and Censored Samples: Theory and Applications. Marcel Dekker, New York (1991)

    MATH  Google Scholar 

  18. Dimitrakopoulou, T., Adamidis, K., Loukas, S.: A life distribution with an upside down bathtub-shaped hazard function. IEEE Trans. Reliab. 56, 308–311 (2007)

    Article  Google Scholar 

  19. Elamir, E.A.H., Seheult, A.H.: Trimmed L-moments. Comput. Stat. Data Anal. 43, 299–314 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  20. Erto, P.: Genesis, properties and identification of the inverse Weibull lifetime model. Statistica Applicato 1, 117–128 (1989)

    Google Scholar 

  21. Falk, M.: On MAD and comedians. Ann. Inst. Stat. Math. 45, 615–644 (1997)

    Article  MathSciNet  Google Scholar 

  22. Filliben, J.J.: Simple and robust linear estimation of the location parameter of a symmetric distribution. Ph.D. thesis, Princeton University, Princeton (1969)

    Google Scholar 

  23. Freimer, M., Mudholkar, G.S., Kollia, G., Lin, C.T.: A study of the generalised Tukey lambda family. Comm. Stat. Theor. Meth. 17, 3547–3567 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  24. Fry, T.R.L.: Univariate and multivariate Burr distributions. Pakistan J. Stat. 9, 1–24 (1993)

    MathSciNet  MATH  Google Scholar 

  25. Galton, F.: Statistics by inter-comparison with remarks on the law of frequency error. Phil. Mag. 49, 33–46 (1875)

    Google Scholar 

  26. Galton, F.: Enquiries into Human Faculty and Its Development. MacMillan, London (1883)

    Book  Google Scholar 

  27. Galton, F.: Natural Inheritance. MacMillan, London (1889)

    Book  Google Scholar 

  28. Gilchrist, W.G.: Statistical Modelling with Quantile Functions. Chapman and Hall/CRC Press, Boca Raton (2000)

    Book  Google Scholar 

  29. Greenwich, M.: A unimodal hazard rate function and its failure distribution. Statistische Hefte 33, 187–202 (1992)

    MATH  Google Scholar 

  30. Greenwood, J.A., Landwehr, J.M., Matalas, N.C., Wallis, J.R.: Probability weighted moments. Water Resour. Res. 15, 1049–1054 (1979)

    Article  Google Scholar 

  31. Groeneveld, R.A., Meeden, G.: Measuring skewness and kurtosis. The Statistician 33, 391–393 (1984)

    Article  Google Scholar 

  32. Gupta, R.C., Akman, H.O., Lvin, S.: A study of log-logistic model in survival analysis. Biometrical J. 41, 431–433 (1999)

    Article  MATH  Google Scholar 

  33. Gupta, R.C., Gupta, P.L., Gupta, R.D.: Modelling failure time data with Lehmann alternative. Comm. Stat. Theor. Meth. 27, 887–904 (1998)

    Article  MATH  Google Scholar 

  34. Gupta, R.C., Gupta, R.D.: Proportional reversed hazards model and its applications. J. Stat. Plann. Infer. 137, 3525–3536 (2007)

    Article  MATH  Google Scholar 

  35. Gupta, R.D., Kundu, D.: Generalized exponential distribution. Aust. New Zeal. J. Stat. 41, 173–178 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  36. Hahn, G.J., Shapiro, S.S.: Statistical Models in Engineering. Wiley, New York (1967)

    Google Scholar 

  37. Hastings, C., Mosteller, F., Tukey, J.W., Winsor, C.P.: Low moments for small samples: A comparative study of statistics. Ann. Math. Stat. 18, 413–426 (1947)

    Article  MathSciNet  MATH  Google Scholar 

  38. Hinkley, D.V.: On power transformations to symmetry. Biometrika 62, 101–111 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  39. Hogben, D.: Some properties of Tukey’s test for non-additivity. Ph.D. thesis, The State University of New Jersey, New Jersey (1963)

    Google Scholar 

  40. Hosking, J.R.M.: L-moments: analysis and estimation of distribution using linear combination of order statistics. J. Roy. Stat. Soc. B 52, 105–124 (1990)

    MathSciNet  MATH  Google Scholar 

  41. Hosking, J.R.M.: Moments or L-moments? An example comparing two measures of distributional shape. The Am. Stat. 46, 186–189 (1992)

    Google Scholar 

  42. Hosking, J.R.M.: Some theoretical results concerning L-moments. Research Report, RC 14492. IBM Research Division, Yorktown Heights, New York (1996)

    Google Scholar 

  43. Hosking, J.R.M.: On the characterization of distributions by their L-moments. J. Stat. Plann. Infer. 136, 193–198 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  44. Hosking, J.R.M.: Some theory and practical uses of trimmed L-moments. J. Stat. Plann. Infer. 137, 3024–3029 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  45. Hosking, J.R.M., Wallis, J.R.: Regional Frequency Analysis: An Approach based on L-Moments. Cambridge University Press, Cambridge (1997)

    Book  Google Scholar 

  46. Joannes, D.L., Gill, C.A.: Comparing measures of sample skewness and kurtosis. The Statistician 47, 183–189 (1998)

    Google Scholar 

  47. Johnson, N.L., Kotz, S., Balakrishnan, N.: Continuous Univariate Distributions, vol. 2, 2nd edn. Wiley, New York (1995)

    Google Scholar 

  48. Joiner, B.L., Rosenblatt, J.R.: Some properties of the range of samples from Tukey’s symmetric lambda distribution. J. Am. Stat. Assoc. 66, 394–399 (1971)

    Article  MATH  Google Scholar 

  49. Jones, M.C.: On some expressions for variance, covariance, skewness and L-moments. J. Stat. Plann. Infer. 126, 97–108 (2004)

    Article  MATH  Google Scholar 

  50. Kececioglu, D.B.: Reliability and Lifetesting Handbook, vol. 1. DEStech Publications, Lancaster (2002)

    Google Scholar 

  51. Kotz, S., Seier, E.: An analysis of quantile measures of kurtosis, center and tails. Stat. Paper. 50, 553–568 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  52. Kus, C.: A new lifetime distribution. Comput. Stat. Data Anal. 51, 4497–4509 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  53. Lai, C.D., Xie, M.: Stochastic Ageing and Dependence for Reliability. Springer, New York (2006)

    MATH  Google Scholar 

  54. Lan, Y., Leemis, L.M.: Logistic exponential survival function. Nav. Res. Logist. 55, 252–264 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  55. Lehmann, E.L.: The power of rank tests. Ann. Math. Stat. 24, 23–42 (1953)

    Article  MATH  Google Scholar 

  56. MacGillivray, H.L.: Skewness properties of asymmetric forms of Tukey-lambda distribution. Comm. Stat. Theor. Meth. 11, 2239–2248 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  57. Marshall, A.W., Olkin, I.: A new method of adding a parameter to a family of distributions with application to exponential and Weibull families. Biometrika 84, 641–652 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  58. Marshall, A.W., Olkin, I.: Life Distributions. Springer, New York (2007)

    MATH  Google Scholar 

  59. Moors, J.J.A.: A quantile alternative for kurtosis. The Statistician 37, 25–32 (1988)

    Article  Google Scholar 

  60. Mudholkar, G.S., Hutson, A.D.: Analogues of L-moments. J. Stat. Plann. Infer. 71, 191–208 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  61. Mudholkar, G.S., Kollia, G.D.: Generalized Weibull family–a structural analysis. Comm. Stat. Theor. Meth. 23, 1149–1171 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  62. Mudholkar, G.S., Srivastava, D.K., Freimer, M.: The exponentiated Weibull family: A reanalysis of bus motor failure data. Technometrics 37, 436–445 (1995)

    Article  MATH  Google Scholar 

  63. Mudholkar, G.S., Srivastava, D.K.: Exponentiated Weibull family for analysing bathtub failure data. IEEE Trans. Reliab. 42, 299–302 (1993)

    Article  MATH  Google Scholar 

  64. Murthy, D.N.P., Xie, M., Jiang, R.: Weibull Models. Wiley, Hoboken (2003)

    Book  Google Scholar 

  65. Paranjpe, S.A., Rajarshi, M.B., Gore, A.P.: On a model for failure rates. Biometrical J. 27, 913–917 (1985)

    Article  Google Scholar 

  66. Parzen, E.: Nonparametric statistical data modelling. J. Am. Stat. Assoc. 74, 105–122 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  67. Parzen, E.: Unifications of statistical methods for continuous and discrete data. In: Page, C., Lepage, R. (eds.) Proceedings of Computer Science-Statistics. INTERFACE 1990, pp. 235–242. Springer, New York (1991)

    Google Scholar 

  68. Parzen, E.: Quality probability and statistical data modelling. Stat. Sci. 19, 652–662 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  69. Pearson, K.: Tables of Incomplete Beta Function, 2nd edn. Cambridge University Press, Cambridge (1968)

    MATH  Google Scholar 

  70. Quetelet, L.A.J.: Letters Addressed to HRH the Grand Duke of Saxe Coburg and Gotha in the Theory of Probability. Charles and Edwin Laton, London (1846). Translated by Olinthus Gregory Downs

    Google Scholar 

  71. Ramberg, J.S.: A probability distribution with applications to Monte Carlo simulation studies. In: Patil, G.P., Kotz, S., Ord, J.K. (eds.) Model Building and Model Selection. Statistical Distributions in Scientific Work, vol. 2. D. Reidel, Dordrecht (1975)

    Google Scholar 

  72. Ramberg, J.S., Dudewicz, E., Tadikamalla, P., Mykytka, E.: A probability distribution and its uses in fitting data. Technometrics 21, 210–214 (1979)

    Article  Google Scholar 

  73. Ramberg, J.S., Schmeiser, B.W.: An approximate method for generating asymmetric random variables. Comm. Assoc. Comput. Mach. 17, 78–82 (1974)

    MathSciNet  MATH  Google Scholar 

  74. Rohatgi, V.K., Saleh, A.K.Md.E.: A class of distributions connected to order statistics with nonintegral sample size. Comm. Stat. Theor. Meth. 17, 2005–2012 (1988)

    Google Scholar 

  75. Sankarasubramonian, A., Sreenivasan, K.: Investigation and comparison of L-moments and conventional moments. J. Hydrol. 218, 13–34 (1999)

    Article  Google Scholar 

  76. Shapiro, S.S., Wilk, M.B.: An analysis of variance test for normality. Biometrika 52, 591–611 (1965)

    MathSciNet  MATH  Google Scholar 

  77. Sillitto, G.P.: Derivation of approximants to the inverse distribution function of a continuous univariate population from the order statistics of a sample. Biometrika 56, 641–650 (1969)

    Article  MATH  Google Scholar 

  78. Stigler, S.M.: Fractional order statistics with applications. J. Am. Stat. Assoc. 72, 544–550 (1977)

    Article  MathSciNet  MATH  Google Scholar 

  79. Suleswki, P.: On differently defined skewness. Comput. Meth. Sci. Technol. 14, 39–46 (2008)

    Google Scholar 

  80. Tajuddin, I.H.: A simple measure of skewness. Stat. Neerl. 50, 362–366 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  81. Tarsitano, A.: Estimation of the generalised lambda distributions parameter for grouped data. Comm. Stat. Theor. Meth. 34, 1689–1709 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  82. Tukey, J.W.: The future of data analysis. Ann. Math. Stat. 33, 1–67 (1962)

    Article  MathSciNet  MATH  Google Scholar 

  83. Tukey, J.W.: Exploratory Data Analysis. Addisson-Wesley, Reading (1977)

    MATH  Google Scholar 

  84. Vogel, R.M., Fennessey, N.M.: L-moment diagrams should replace product moment diagrams. Water Resour. Res. 29, 1745–1752 (1993)

    Article  Google Scholar 

  85. Xie, M., Tang, Y., Goh, T.N.: A modified Weibull extension with bathtub-shaped failure rate function. Reliab. Eng. Syst. Saf. 76, 279–285 (2002)

    Article  Google Scholar 

  86. Yitzhaki, S.: Gini’s mean difference: A superior measure of variability for nonnormal distributions. Metron 61, 285–316 (2003)

    MathSciNet  Google Scholar 

  87. Zimmer, W., Keats, J.B., Wang, F.K.: The Burr XII distribution in reliability analysis. J. Qual. Technol. 20, 386–394 (1998)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media New York

About this chapter

Cite this chapter

Nair, N.U., Sankaran, P.G., Balakrishnan, N. (2013). Quantile Functions. In: Quantile-Based Reliability Analysis. Statistics for Industry and Technology. Birkhäuser, New York, NY. https://doi.org/10.1007/978-0-8176-8361-0_1

Download citation

Publish with us

Policies and ethics