Abstract
To execute the multiple comparison methods introduced in Chaps. 1–4, we need the upper \(100\alpha \%\) points for the distributions of the statistics. For cases with no order constraints on k means (see Chaps. 1, 2, and 4), we can use executable programs listed in Appendix B of Shiraishi (Multiple comparison procedures under continuous distributions. Kyoritsu Shuppan Co., Ltd., 2011) for the values of the upper \(100\alpha \%\) points of the distributions. On the other hand, when there are order constraints on the location parameters introduced in Chap. 3, the multiple comparison methods require more complicated numerical calculations for the statistical distribution. The distributions in these cases are derived from the normal distribution. The key objective of the numerical calculation is the integral transformation of the Gaussian function. We set the function family \(\mathbf {G}\) as a generalization of the Gaussian function and introduce Sinc approximation method suitable for the approximation and calculus of functions belonging to \(\mathbf {G}\). As a specific application, in Sect. 7.2, we introduce calculation methods concerning the distribution function of the Hayter type statistics, which is the distribution of the max statistics in Chap. 3. Then, in Sect. 7.3, we introduce a numerical method to calculate the level probability for the multiple comparison methods that is based on the sum-of-squares statistics described in Sect. 3.3. The proofs for the theorems are not presented in this chapter. Please visit the following webpage for the proofs: http://www.st.nanzan-u.ac.jp/info/sugiurah/sincstatistics.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abramowitz M, Stegun IA (1972) Handbook of mathematical functions. Dover, New York
Barlow RE, Bartholomew DJ, Bremner JM, Brunk HD (1972) Statistical inference under order restrictions. Wiley, London
Hayter AJ, Liu W (1996) On the exact calculation of the one-sided studentized range test. Comput Stat Data Anal 22:17–25
Lund J, Bowers KL (1992) Sinc methods for quadrature and differential equations. SIAM, Philadelphia
Ralston A, Rabinowitz P (1978) First course in numerical analysis, 2nd edn. Dover, New York
Robertson T, Wright FT, Dykstra RL (1988) Order restricted statistical inference. Wiley, New York
Shiraishi T (2011) Multiple comparison procedures under continuous distributions. Kyoritsu-Shuppan Co., Ltd. (in Japanese)
Shiraishi T, Sugiura H (2018) Theory of multiple comparison procedures and its computation. Kyoritsu-Shuppan Co., Ltd. (in Japanese)
Stenger F (1993) Numerical methods based on sinc and analytic function. Springer, Berlin
Takahashi H, Mori M (1974) Double exponential formulas for numerical integration. Publ Res Inst Math Sci 9:721–741
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2019 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Shiraishi, Ta., Sugiura, H., Matsuda, Si. (2019). Computation of Distribution Functions for Statistics Under Simple Order Restrictions. In: Pairwise Multiple Comparisons. SpringerBriefs in Statistics(). Springer, Singapore. https://doi.org/10.1007/978-981-15-0066-4_7
Download citation
DOI: https://doi.org/10.1007/978-981-15-0066-4_7
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-0065-7
Online ISBN: 978-981-15-0066-4
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)