LEADER 02840oam 2200481 450 001 996418201603316 005 20210610214459.0 010 $a981-15-9663-8 024 7 $a10.1007/978-981-15-9663-6 035 $a(CKB)5460000000008690 035 $a(DE-He213)978-981-15-9663-6 035 $a(MiAaPQ)EBC6450865 035 $a(PPN)253250951 035 $a(EXLCZ)995460000000008690 100 $a20210610d2021 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aPioneering works on distribution theory $ein honor of Masaaki Sibuya /$fNobuaki Hoshino, Shuhei Mano, Takaaki Shimura, editors 205 $a1st ed. 2020. 210 1$aGateway East, Singapore :$cSpringer,$d[2021] 210 4$d©2021 215 $a1 online resource (VII, 121 p. 22 illus., 1 illus. in color.) 225 1 $aJSS Research Series in Statistics,$x2364-0057 311 $a981-15-9662-X 327 $aGibbs Base Random Partitions -- Asymptotic and approximate discrete distributions for length of Ewens sampling formula -- An Error Bound for the Normal Approximation to the Length of a Ewens Partition -- Distribution of Number of Levels in [s]-specified Random Permutation -- Properties of General Systems of Orthogonal Polynomials with Symmetric Matrix Argument -- Conjugate Analysis under Jeffreys' Prior with its Implications to Likelihood Inference. 330 $aThis book highlights the forefront of research on statistical distribution theory, with a focus on unconventional random quantities, and on phenomena such as random partitioning. The respective papers reflect the continuing appeal of distribution theory and the lively interest in this classic field, which owes much of its expansion since the 1960s to Professor Masaaki Sibuya, to whom this book is dedicated. The topics addressed include a test procedure for discriminating the (multivariate) Ewens distribution from the Pitman Sampling Formula, approximation to the length of the Ewens distribution by discrete distributions and the normal distribution, and the distribution of the number of levels in [s]-specified random permutations. Also included are distributions associated with orthogonal polynomials with a symmetric matrix argument and the characterization of the Jeffreys prior. 410 0$aJSS Research Series in Statistics,$x2364-0057 606 $aDistribution (Probability theory) 615 0$aDistribution (Probability theory) 676 $a519.24 702 $aHoshino$b Nobuaki 702 $aMano$b Shuhei 702 $aShimura$b Takaaki 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bUtOrBLW 906 $aBOOK 912 $a996418201603316 996 $aPioneering works on distribution theory$92066355 997 $aUNISA