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BY-NC-ND 3.0 license Open Access Published by De Gruyter Open Access December 15, 2016

Characterizations of the distribution of the Demmel condition number of real Wishart matrices

  • M. Shakil and M. Ahsanullah
From the journal Special Matrices

Abstract

The Demmel condition number is an indicator of the matrix condition, and its properties have recently found applications in many practical problems, such as in MIMO communication systems, in the analytical prediction of level-crossing and fade duration statistics of Rayleigh channels, and in spectrum sensing for cognitive radio systems, among others. As the characterizations of a probability distribution play an important role in probability and statistics, in this paper we study the characterizations of the distribution of the Demmel condition number of real Wishart matrices by truncated first moment. Since the truncated distributions arise in practical statistics where the ability of record observations is limited to a given threshold or within a specified range, we hope that these characterizations will be quite useful for practitioners and researchers in the fields of probability, statistics, and other applied sciences, such as actuarial science, linear algebra, multivariate statistics, physics, wireless communications, among others.

References

[1] Abramowitz, M., and Stegun, I. A. (1970). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. National Bureau of Standards, Washington, D. C. Search in Google Scholar

[2] Ahsanullah, M., Shakil, M., and Kibria, B. M. G. (2013). On a probability distribution with fractional moments arising from generalized Pearson system of differential equation and its characterization. International Journal of Advanced Statistics and Probability, 1(3), 132 - 141. 10.14419/ijasp.v1i3.1435Search in Google Scholar

[3] Ahsanullah, M., Kibria, B. M. G., and Shakil, M. (2014). Normal and Student´s t Distributions and Their Applications. Atlantis Press, Paris, France. Search in Google Scholar

[4] Anderson,W., and Wells, M. T. (2009). The exact distribution of the condition number of a Gaussianmatrix. SIAM Journal on Matrix Analysis and Applications, 31 (3), 1125 - 1130. Search in Google Scholar

[5] Blum, L., and Shub, M. (1986). Evaluating rational functions: infinite precision is finite cost and tractable on average. SIAM Journal on Computing, 15 (2), 384 - 398. 10.1137/0215026Search in Google Scholar

[6] Bühlmann, H. (1967). Experience rating and credibility. Astin Bulletin, 4(03), 199 - 207. 10.1017/S0515036100008989Search in Google Scholar

[7] Chen, Z., and Dongarra, J. J. (2005). Condition numbers of Gaussian random matrices. SIAM Journal on Matrix Analysis and Applications, 27(3), 603 - 620. 10.1137/040616413Search in Google Scholar

[8] Cottone, G., and Di Paola, M. (2009). On the use of fractional calculus for the probabilistic characterization of random variables. Probabilistic Engineering Mechanics, 24(3), 321 - 330. 10.1016/j.probengmech.2008.08.002Search in Google Scholar

[9] Cottone, G., Di Paola, M., and Metzler, R. (2010). Fractional calculus approach to the statistical characterization of random variables and vectors. Physica A: Statistical Mechanics and its Applications, 389(5), 909 - 920. 10.1016/j.physa.2009.11.018Search in Google Scholar

[10] Demmel, J. W. (1988). The probability that a numerical analysis problem is difficult. Mathematics of Computation, 50 (182), 449 - 480. 10.1090/S0025-5718-1988-0929546-7Search in Google Scholar

[11] Edelman, A. (1988). Eigenvalues and condition numbers of random matrices. SIAM Journal on Matrix Analysis and Applications, 9 (4), 543 - 560. 10.1137/0609045Search in Google Scholar

[12] Edelman, A. (1992). On the distribution of a scaled condition number. Mathematics of Computation, 58(197), 185 - 190. 10.1090/S0025-5718-1992-1106966-2Search in Google Scholar

[13] Edelman, A., and Rao, N. R. (2005). Random matrix theory. Acta Numerica, 14, 233 - 297. 10.1017/S0962492904000236Search in Google Scholar

[14] Edelman, A., and Wang, Y. (2013). Random matrix theory and its innovative applications. In Advances in Applied Mathematics, Modeling, and Computational Science, 91 - 116. Springer, USA. 10.1007/978-1-4614-5389-5_5Search in Google Scholar

[15] Galambos, J., and Kotz, S. (1978). Characterizations of probability distributions. A unified approach with an emphasis on exponential and related models, Lecture Notes in Mathematics, 675, Springer, Berlin. 10.1007/BFb0069530Search in Google Scholar

[16] Glänzel, W. (1987). A characterization theorem based on truncated moments and its application to some distribution families, Mathematical Statistics and Probability Theory (Bad Tatzmannsdorf, 1986), Vol. B, Reidel, Dordrecht, 75 – 84. Search in Google Scholar

[17] Glänzel, W., Telcs, A., and Schubert, A. (1984). Characterization by truncated moments and its application to Pearson-type distributions, Z. Wahrsch. Verw. Gebiete, 66, 173 – 183. 10.1007/BF00531527Search in Google Scholar

[18] Gradshteyn, I. S., and Ryzhik, I. M. (1980). Table of integrals, series, and products, Academic Press, Inc., San Diego, California, USA. Search in Google Scholar

[19] Haagerup, U., and Thorbjrrnsen, S. (2003). Random matrices with complex Gaussian entries. Expositiones Mathematicae, 21(4), 293 - 337. 10.1016/S0723-0869(03)80036-1Search in Google Scholar

[20] Khuri, A.I. (1993). Advanced Calculus with Applications in Statistics, John Wiley & Sons, New York, USA. Search in Google Scholar

[21] Kim, J. H., and Jeon, Y. (2013). Credibility theory based on trimming. Insurance: Mathematics and Economics, 53(1), 36 - 47. 10.1016/j.insmatheco.2013.03.012Search in Google Scholar

[22] Kotz, S., and Shanbhag, D. N. (1980). Some new approaches to probability distributions. Advances in Applied Probability, 12, 903 - 921. 10.2307/1426748Search in Google Scholar

[23] Oldham, K. B.,Myland, J., and Spanier, J. (2009). An Atlas of Functions with Equator, the Atlas Function Calculator. Springer, New York, USA. Search in Google Scholar

[24] Prudnikov, A. P., Brychkov, Y. A. and Marichev, O. I. (1986). Integrals and Series, Volumes 1, 2, and 3. Gordon and Breach Science Publishers, Amsterdam. Search in Google Scholar

[25] Shakil, M., Kibria, B. G., and Chang, K. C. (2008). Distributions of the product and ratio of Maxwell and Rayleigh random variables. Statistical Papers, 49(4), 729 - 747. 10.1007/s00362-007-0052-9Search in Google Scholar

[26] Wei, L., McKay, M. R., & Tirkkonen, O. (2011). Exact Demmel condition number distribution of complex Wishart matrices via the Mellin transform. IEEE Communications Letters, 15(2), 175-177. 10.1109/LCOMM.2010.121310.101590Search in Google Scholar

[27] Weiss, G. H., Havlin, S., and Matan, O. (1989). Properties of noninteger moments in a first passage time problem. Journal of Statistical Physics, 55 (1 - 2), 435 - 439. 10.1007/BF01042610Search in Google Scholar

[28] Wigner, E. (955). Characteristic Vectors of Bordered Matrices with Infinite Dimensions. Annals of Mathematics, 62 (3), 548 - 564. 10.2307/1970079Search in Google Scholar

[29] Wishart, J. (1928). The generalised product moment distribution in samples from a normal multivariate population. Biometrika, 32 - 52. 10.1093/biomet/20A.1-2.32Search in Google Scholar

[30] Zhang, W., Wang, C.-X., Tao, X., and Patcharamaneepakorn, P. Exact Distributions of Finite Random Matrices and Their Applications to Spectrum Sensing. Sensors 2016, 16, 1183. 10.3390/s16081183Search in Google Scholar PubMed PubMed Central

[31] Zhong, C., McKay, M. R., Ratnarajah, T., and Wong, K. K. (2011). Distribution of the Demmel condition number of Wishart matrices. IEEE Transactions on Communications, 59 (5), 1309 - 1320. 10.1109/TCOMM.2011.040111.100137Search in Google Scholar

Received: 2016-1-12
Accepted: 2016-11-28
Published Online: 2016-12-15

©2016 M. Shakil and M. Ahsanullah

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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