Gibbs Sampling, Exponential Families and Orthogonal Polynomials
Persi Diaconis, Kshitij Khare, and Laurent Saloff-Coste
Source: Statist. Sci. Volume 23, Number 2
(2008), 151-178.
Abstract
We give families of examples where sharp rates of convergence to stationarity of the widely used Gibbs sampler are available. The examples involve standard exponential families and their conjugate priors. In each case, the transition operator is explicitly diagonalizable with classical orthogonal polynomials as eigenfunctions.
First Page:
Show
Hide
Keywords: Gibbs sampler; running time analyses; exponential families; conjugate priors; location families; orthogonal polynomials; singular value decomposition
Full-text: Open access
Links and Identifiers
Permanent link to this document: http://projecteuclid.org/euclid.ss/1219339107
Digital Object Identifier: doi:10.1214/07-STS252
Mathematical Reviews number (MathSciNet): MR2446500
References
[1] Akhiezer, N. and Glazman, I. (1993). Theory of Linear Operators in Hilbert Space. Dover, New York.
Mathematical Reviews (MathSciNet): MR1255973
[2] Amit, Y. (1996). Convergence properties of the Gibbs sampler for perturbations of Gaussians. Ann. Statist. 24 122–140.
Mathematical Reviews (MathSciNet): MR1389883
Zentralblatt MATH: 0854.60066
Digital Object Identifier: doi:10.1214/aos/1033066202
Project Euclid: euclid.aos/1033066202
[3] Anderson, W. (1991). Continuous-Time Markov Chains. An Applications-Oriented Approach. Springer, New York.
Mathematical Reviews (MathSciNet): MR1118840
[4] Athreya, K., Doss, H. and Sethuraman, J. (1996). On the convergence of the Markov chain simulation method. Ann. Statist. 24 89–100.
Mathematical Reviews (MathSciNet): MR1389881
Zentralblatt MATH: 0860.60057
Digital Object Identifier: doi:10.1214/aos/1033066200
Project Euclid: euclid.aos/1033066200
[5] Baik, J., Kriecherbauer, T., McLaughlin, K. and Miller, P. (2003). Uniform asymptotics for polynomials orthogonal with respect to a general class of weights and universality results for associated ensembles. Intern. Math. Res. Not. 15 821–858.
Mathematical Reviews (MathSciNet): MR1952523
Zentralblatt MATH: 1036.42023
Digital Object Identifier: doi:10.1155/S1073792803212125
[6] Bakry, D. and Mazet, O. (2003). Characterization of Markov semigroups on ℝ associated to some families of orthogonal polynomials. Séminaire de Probabilités XXXVII 60–80. Lecture Notes in Math. 1832. Springer, Berlin.
Mathematical Reviews (MathSciNet): MR2053041
Zentralblatt MATH: 1060.33014
[7] Bar-Lev, S., Bshouty, D., Enis, P., Letac, G., Lu, I.-L. and Richards, D. (1994). The diagonal multivariate natural exponential families and their classification. J. Theoret. Probab. 7 883–929.
Mathematical Reviews (MathSciNet): MR1295545
Zentralblatt MATH: 0807.60017
Digital Object Identifier: doi:10.1007/BF02214378
[8] Barndorff-Nielsen, O. (1978). Information and Exponential Families in Statistical Theory. Wiley, Chichester.
Mathematical Reviews (MathSciNet): MR489333
Zentralblatt MATH: 0387.62011
[9] Baxendale, P. (2005). Renewal theory and computable convergence rates for geometrically ergodic Markov chains. Ann. Appl. Probab. 15 700–738.
Mathematical Reviews (MathSciNet): MR2114987
Digital Object Identifier: doi:10.1214/105051604000000710
Project Euclid: euclid.aoap/1107271665
[10] Ben Arous, G., Bovier, A. and Gayard, V. (2003). Glauber dynamics of the random energy model. I, II. Comm. Math Phys. 235 379–425, 236 1–54.
[11] Brown, L. (1986). Fundamentals of Statistical Exponential Families. IMS, Hayward, CA.
[12] Bryc, W. (2006). Approximation operators, exponential, and free exponential families. Preprint, Dept. Math. Sci., Univ. Cincinnati.
[13] Buja, A. C. (1990). Remarks on functional canonical variates, alternating least square methods and ACE. Ann. Statist. 18 1032–1069.
Mathematical Reviews (MathSciNet): MR1062698
Zentralblatt MATH: 0721.62068
Digital Object Identifier: doi:10.1214/aos/1176347739
Project Euclid: euclid.aos/1176347739
[14] Cannings, C. (1974). The latent roots of certain Markov chains asrising in genetics: A new approach. I. Haploid models. Adv. in Appl. Probab. 6 260–290.
Mathematical Reviews (MathSciNet): MR343949
Zentralblatt MATH: 0284.60064
Digital Object Identifier: doi:10.2307/1426293
JSTOR: links.jstor.org
[15] Casalis, M. (1996). The 2d+4 simple quadratic families on Rd. Ann. Statist. 24 1828–1854.
Mathematical Reviews (MathSciNet): MR1416663
Zentralblatt MATH: 0867.62042
Digital Object Identifier: doi:10.1214/aos/1032298298
Project Euclid: euclid.aos/1032298298
[16] Casella, G. and George, E. (1992). Explaining the Gibbs sampler. Amer. Statist. 46 167–174.
Mathematical Reviews (MathSciNet): MR1183069
Digital Object Identifier: doi:10.2307/2685208
JSTOR: links.jstor.org
[17] Chamayou, J. and Letac, G. (1991). Explicit stationary distributions for compositions of random functions and products of random matrices. J. Theoret. Probab. 4 3–36.
Mathematical Reviews (MathSciNet): MR1088391
Zentralblatt MATH: 0728.60012
Digital Object Identifier: doi:10.1007/BF01046992
[18] Chihara, T. (1978). An Introduction to Orthogonal Polynomials. Gordon and Breach, New York.
Mathematical Reviews (MathSciNet): MR481884
Zentralblatt MATH: 0389.33008
[19] Consonni, G. and Veronese, P. (1992). Conjugate priors for exponential families having quadratic variance functions. J. Amer. Statist. Assoc. 87 1123–1127.
Mathematical Reviews (MathSciNet): MR1209570
Zentralblatt MATH: 0764.62027
Digital Object Identifier: doi:10.2307/2290650
JSTOR: links.jstor.org
[20] Cooper, R., Hoare, M. and Rahman, M. (1977). Stochastic Processes and special functions: On the probabilistic origin of some positive kernels associated with classical orthogonal polynomials. J. Math. Anal. Appl. 61 262–291.
Mathematical Reviews (MathSciNet): MR486694
Digital Object Identifier: doi:10.1016/0022-247X(77)90160-3
[21] Dauxois, J. and Pousse, A. (1975). Une extension de l’analyse canonique. Quelques applications. Ann. Inst. H. Poincaré Sect. B (N.S.) 11 355–379.
Mathematical Reviews (MathSciNet): MR408118
[22] Deutsch, F. (2001). Best Approximation in Inner Product Spaces. Springer, New York.
Mathematical Reviews (MathSciNet): MR1823556
[23] Diaconis, P. and Freedman, D. (1999). Iterated random functions. SIAM Rev. 41 45–76.
Mathematical Reviews (MathSciNet): MR1669737
Zentralblatt MATH: 0926.60056
Digital Object Identifier: doi:10.1137/S0036144598338446
JSTOR: links.jstor.org
[24] Diaconis, P., Khare, K. and Saloff-Coste, L. (2006). Stochastic alternating projections. Preprint, Dept. Statistics, Stanford Univ.
[25] Diaconis, P., Khare, K. and Saloff-Coste, L. (2006). Gibbs sampling, exponential families and coupling. Preprint, Dept. of Statistics, Stanford Univ.
[26] Diaconis, P. and Saloff-Coste, L. (1993). Comparison theorems for Markov chains. Ann. Appl. Probab. 3 696–730.
Mathematical Reviews (MathSciNet): MR1233621
Zentralblatt MATH: 0799.60058
Digital Object Identifier: doi:10.1214/aoap/1177005359
Project Euclid: euclid.aoap/1177005359
[27] Diaconis, P. and Saloff-Coste, L. (2006). Separation cut-offs for birth and death chains. Ann. Appl. Probab. 16 2098–2122.
Mathematical Reviews (MathSciNet): MR2288715
Zentralblatt MATH: 1127.60081
Digital Object Identifier: doi:10.1214/105051606000000501
Project Euclid: euclid.aoap/1169065218
[28] Diaconis, P. and Stanton, D. (2006). A hypergeometric walk. Preprint, Dept. Statistics, Stanford Univ.
[29] Diaconis, P. and Ylvisaker, D. (1979). Conjugate priors for exponential families. Ann. Statist. 7 269–281.
Mathematical Reviews (MathSciNet): MR520238
Zentralblatt MATH: 0405.62011
Digital Object Identifier: doi:10.1214/aos/1176344611
Project Euclid: euclid.aos/1176344611
[30] Diaconis, P. and Ylvisaker, D. (1985). Quantifying prior opinion. In Bayesian Statistics 2 (J. Bernardo et al. eds.) 133–156. North-Holland, Amsterdam.
Mathematical Reviews (MathSciNet): MR862488
Zentralblatt MATH: 0673.62004
[31] Donoho, D. and Johnstone, I. (1989). Projection-based approximation and a duality with kernel methods. Ann. Statist. 17 58–106.
Mathematical Reviews (MathSciNet): MR981438
Zentralblatt MATH: 0699.62067
Digital Object Identifier: doi:10.1214/aos/1176347004
Project Euclid: euclid.aos/1176347004
[32] Dyer, M., Goldberg, L., Jerrum, M. and Martin, R. (2005). Markov chain comparison. Probab. Surv. 3 89–111.
Mathematical Reviews (MathSciNet): MR2216963
Digital Object Identifier: doi:10.1214/154957806000000041
Project Euclid: euclid.ps/1145890796
[33] Eaton, M. L. (1992). A statistical diptych: Admissible inferences—Recurrence of symmetric Markov chains. Ann. Statist. 20 1147–1179.
Mathematical Reviews (MathSciNet): MR1186245
Zentralblatt MATH: 0767.62002
Digital Object Identifier: doi:10.1214/aos/1176348764
Project Euclid: euclid.aos/1176348764
[34] Eaton, M. L. (1997). Admissibility in quadratically regular problems and recurrence of symmetric Markov chains: Why the connection? J. Statist. Plann. Inference 64 231–247.
Mathematical Reviews (MathSciNet): MR1621615
Zentralblatt MATH: 0944.62010
Digital Object Identifier: doi:10.1016/S0378-3758(97)00037-2
[35] Eaton, M. L. (2001). Markov chain conditions for admissibility on estimation problems with quadratic loss. In State of the Art in Statistics and Probability. A Festschrift for Willen von Zwet (M. de Gunst, C. Klaassen and A. van der Vrad, eds.) 223–243. IMS, Beachwood, OH.
Mathematical Reviews (MathSciNet): MR1836563
Digital Object Identifier: doi:10.1214/lnms/1215090071
[36] Eagleson, G. (1964). Polynomial expansions of bivariate distributions. Ann. Math. Statist. 25 1208–1215.
Mathematical Reviews (MathSciNet): MR168055
Zentralblatt MATH: 0126.35402
Digital Object Identifier: doi:10.1214/aoms/1177703278
Project Euclid: euclid.aoms/1177703278
[37] Esch, D. (2003). The skew-t distribution: Properties and computations. Ph.D. dissertation, Dept. Statistics, Harvard Univ.
[38] Ewens, W. (2004). Mathematical Population Genetics. I. Theoretical Introduction, 2nd ed. Springer, New York.
Mathematical Reviews (MathSciNet): MR2026891
Zentralblatt MATH: 1060.92046
[39] Feinsilver, P. (1986). Some classes of orthogonal polynomials associated with martingales. Proc. Amer. Math. Soc. 98 298–302.
Mathematical Reviews (MathSciNet): MR854037
Zentralblatt MATH: 0615.60050
Digital Object Identifier: doi:10.2307/2045702
JSTOR: links.jstor.org
[40] Feinsilver, P. (1991). Orthogonal polynomials and coherent states. In Symmetries in Science V 159–172. Plenum Press, New York.
Mathematical Reviews (MathSciNet): MR1143591
[41] Feinsilver, P. and Schott, R. (1993). Algebraic Structures and Operator Calculus. I. Representations and Probability Theory. Kluwer Academic Press, Dordrecht.
Mathematical Reviews (MathSciNet): MR1227095
[42] Feller, W. (1951). Diffusion processes in genetics. Proc. Second Berkeley Symp. Math. Statist. Probab. 227–246. Univ. California Press, Berkeley.
Mathematical Reviews (MathSciNet): MR46022
Zentralblatt MATH: 0045.09302
[43] Feller, W. (1968). An Introduction to Probability Theory and Its Applications. I, 3rd ed. Wiley, New York.
Mathematical Reviews (MathSciNet): MR228020
[44] Feller, W. (1971). An Introduction to Probability Theory and Its Applications. II, 2nd ed. Wiley, New York.
[45] Gelfand, A. E. and Smith, A. F. M. (1990). Sampling based approaches to calculating marginal densities. J. Amer. Statist. Assoc. 85 398–409.
Mathematical Reviews (MathSciNet): MR1141740
Zentralblatt MATH: 0702.62020
Digital Object Identifier: doi:10.2307/2289776
JSTOR: links.jstor.org
[46] Geman, S. and Geman, D. (1984). Stochastic relaxation Gibbs distributions and the Bayesian restoration of images. IEEE Trans. Pattern Anal. Machine Intelligence 6 721–741.
[47] Gilks, W. Richardson, S. and Spiegelhalter, D. (1996). Markov Chain Monte Carlo in Practice. Chapman and Hall, London.
Mathematical Reviews (MathSciNet): MR1397966
[48] Gill, J. (2002). Bayesian Methods: A Social and Behavioral Sciences Approach. Chapman and Hall, Boca Raton, FL.
[49] Glauber, R. (1963). Time dependent statistics of the Ising model. J. Math. Phys. 4 294–307.
Mathematical Reviews (MathSciNet): MR148410
Zentralblatt MATH: 0145.24003
Digital Object Identifier: doi:10.1063/1.1703954
[50] Goodman, J. and Sokal, A. (1984). Multigrid Monte Carlo method conceptual foundations. Phys. Rev. D 40 2035–2071.
[51] Griffiths, R. C. (1971). Orthogonal polynomials on the multinomial distribution. Austral. J. Statist. 13 27–35.
Mathematical Reviews (MathSciNet): MR275548
Digital Object Identifier: doi:10.1111/j.1467-842X.1971.tb01239.x
[52] Griffiths, R. C. (1978). On a bivariate triangular distribution. Austral. J. Statist. 20 183–185.
Mathematical Reviews (MathSciNet): MR548185
Zentralblatt MATH: 0412.60016
Digital Object Identifier: doi:10.1111/j.1467-842X.1978.tb01304.x
[53] Griffiths, R. C. (2006). n-kernel orthogonal polynomials on the Dirichlet, Dirichlet-multinomial, Ewens’ sampling distribution and Poisson Dirichlet processes. Lecture notes available at http://www.stats.ox.ac.uk/~griff/.
[54] Gross, L. (1979). Decay of correlations in classical lattice models at high temperatures. Comm. Math. Phys. 68 9–27.
Mathematical Reviews (MathSciNet): MR539733
Zentralblatt MATH: 0442.60097
Digital Object Identifier: doi:10.1007/BF01562538
Project Euclid: euclid.cmp/1103905263
[55] Gutierrez-Pena, E. and Smith, A. (1997). Exponential and Bayes in conjugate families: Review and extensions. Test 6 1–90.
Mathematical Reviews (MathSciNet): MR1466433
Zentralblatt MATH: 0891.62017
Digital Object Identifier: doi:10.1007/BF02564426
[56] Harkness, W. and Harkness, M. (1968). Generalized hyperbolic secant distributions. J. Amer. Statist. Assoc. 63 329–337.
Mathematical Reviews (MathSciNet): MR234503
Zentralblatt MATH: 0155.27204
Digital Object Identifier: doi:10.2307/2283852
JSTOR: links.jstor.org
[57] Hassairi, A. and Zarai, M. (2004). Characterization of the cubic exponential families by orthogonality of polynomials. Ann. Statist. 32 2463–2476.
Mathematical Reviews (MathSciNet): MR2078547
Zentralblatt MATH: 1056.62015
Digital Object Identifier: doi:10.1214/009117904000000522
Project Euclid: euclid.aop/1091813620
[58] Hoare, M. and Rahman, M. (1979). Distributed processes in discrete systems. Physica 97A 1–41.
[59] Hoare, M. and Rahman, M. (1983). Cumulative Bernoulli trials and Krawtchouk processes. Stochastic Process. Appl. 16 113–139.
Mathematical Reviews (MathSciNet): MR724060
Zentralblatt MATH: 0534.60060
Digital Object Identifier: doi:10.1016/0304-4149(84)90014-0
[60] Hoare, M. and Rahman, M. (2007). A probabilistic origin for a new class of bivariate polynomials. Preprint, School of Math. and Stat. Carleton Univ., Ottawa.
[61] Hobert, J. P. and Robert, C. P. (1999). Eaton’s Markov chain, its conjugate partner and P-admissibility. Ann. Statist. 27 361–373.
Mathematical Reviews (MathSciNet): MR1701115
Zentralblatt MATH: 0945.62012
Digital Object Identifier: doi:10.1214/aos/1018031115
Project Euclid: euclid.aos/1018031115
[62] Ismail, M. (1977). Connection relations and bilinear formulas for the classical orthogonal polynomials. J. Math. Anal. Appl. 57 487–496.
Mathematical Reviews (MathSciNet): MR430361
Zentralblatt MATH: 0346.33016
Digital Object Identifier: doi:10.1016/0022-247X(77)90241-4
[63] Ismail, M. (2005). Classical and Quantum Orthogonal Polynomials. Cambridge Univ. Press.
Mathematical Reviews (MathSciNet): MR2191786
[64] Jones, G. and Hobert, J. (2001). Honest exploration of intractable probability distributions via Markov chain Monte Carlo. Statist. Sci. 16 312–334.
Mathematical Reviews (MathSciNet): MR1888447
Digital Object Identifier: doi:10.1214/ss/1015346317
Project Euclid: euclid.ss/1015346317
[65] Jones, G. L. and Hobert, J. P. (2004). Sufficient burn-in for Gibbs samplers for a hierarchical random effects model. Ann. Statist. 32 784–817.
Mathematical Reviews (MathSciNet): MR2060178
Zentralblatt MATH: 1048.62069
Digital Object Identifier: doi:10.1214/009053604000000184
Project Euclid: euclid.aos/1083178947
[66] Jorgensen, C. (1997). The Theory of Dispersion Models. Chapman and Hall, London.
Mathematical Reviews (MathSciNet): MR1462891
[67] Karlin, S. and McGregor, J. (1961). The Hahn polynomials, formulas and application. Scripta. Math. 26 33–46.
Mathematical Reviews (MathSciNet): MR138806
Zentralblatt MATH: 0104.29103
[68] Koekoek, R. and Swarttouw, R. (1998). The Askey-scheme of hypergeometric orthogonal polynomials and its q-analog. Available at http://math.nist.gov/opsf/projects/koekoek.html.
[69] Koudou, A. and Pommeret, D. (2000). A construction of Lancaster probabilities with margins in the multidimensional Meixner class. Austr. N. Z. J. Stat. 42 59–66.
Mathematical Reviews (MathSciNet): MR1747462
[70] Koudou, A. (1996). Probabilities de Lancaster. Exp. Math. 14 247–275.
Mathematical Reviews (MathSciNet): MR1409004
[71] Koudou, A. (1998). Lancaster bivariate probability distributions with Poisson, negative binomial and gamma margins. Test 7 95–110.
Mathematical Reviews (MathSciNet): MR1650839
Zentralblatt MATH: 0947.60014
Digital Object Identifier: doi:10.1007/BF02565104
[72] Lancaster, H. O. (1969). The Chi-Squared Distribution. Wiley, New York.
Mathematical Reviews (MathSciNet): MR253452
Zentralblatt MATH: 0193.17802
[73] Lehmann, E. and Romano, J. (2005). Testing Statistical Hypotheses, 3rd ed. Springer, New York.
Mathematical Reviews (MathSciNet): MR2135927
[74] Letac, G. (1992). Lectures on Natural Exponential Families and Their Variance Functions. Monografías de Matemática 50. IMPA, Rio de Janeiro.
[75] Letac, G. (2002). Donkey walk and Dirichlet distributions. Statist. Probab. Lett. 57 17–22.
Mathematical Reviews (MathSciNet): MR1911808
[76] Letac, G. and Mora, M. (1990). Natural real exponential families with cubic variance functions. Ann. Statist. 18 1–37.
Mathematical Reviews (MathSciNet): MR1041384
Zentralblatt MATH: 0714.62010
Digital Object Identifier: doi:10.1214/aos/1176347491
Project Euclid: euclid.aos/1176347491
[77] Liu, J., Wong, W. and Kong, A. (1995). Covariance structure and convergence rates of the Gibbs sampler with various scans. J. Roy. Statist. Soc. Ser. B 57 157–169.
Mathematical Reviews (MathSciNet): MR1325382
JSTOR: links.jstor.org
[78] Liu, J. (2001). Monte Carlo Strategies in Scientific Computing. Springer, New York.
Mathematical Reviews (MathSciNet): MR1842342
[79] Malouche, D. (1998). Natural exponential families related to Pick functions. Test 7 391–412.
Mathematical Reviews (MathSciNet): MR1667006
Zentralblatt MATH: 0935.60006
Digital Object Identifier: doi:10.1007/BF02565120
[80] Mckenzie, E. (1988). Some ARMA models for dependent sequences of Poisson counts. Adv. in Appl. Probab. 20 822–835.
Mathematical Reviews (MathSciNet): MR968000
Zentralblatt MATH: 0664.62089
Digital Object Identifier: doi:10.2307/1427362
JSTOR: links.jstor.org
[81] Marchev, D. and Hobert, J. P. (2004). Geometric ergodicity of van Dyk and Meng’s algorithm for the multivariate Student’s t model. J. Amer. Statist. Assoc. 99 228–238.
Mathematical Reviews (MathSciNet): MR2054301
Zentralblatt MATH: 1089.60518
Digital Object Identifier: doi:10.1198/016214504000000223
[82] Meng, X. L. and Zaslavsky, A. (2002). Single observation unbiased priors. Ann. Statist. 30 1345–1375.
Mathematical Reviews (MathSciNet): MR1936322
Zentralblatt MATH: 1019.62024
Digital Object Identifier: doi:10.1214/aos/1035844979
Project Euclid: euclid.aos/1035844979
[83] Meixner, J. (1934). Orthogonal polynom system mit einer Besonderth Gestalt der Erzengerder function. J. London Math. Soc. 9 6–13.
[84] Meyer, P. A. (1966). Probability and Potentials. Blaisdell, Waltham, MA.
Mathematical Reviews (MathSciNet): MR205288
[85] Moreno, E. and Girón, F. (1998). Estimating with incomplete count data: A Bayesian approach. J. Statist. Plann. Inference 66 147–159.
[86] Morris, C. (1982). Natural exponential families with quadratic variance functions. Ann. Statist. 10 65–80.
Mathematical Reviews (MathSciNet): MR642719
Digital Object Identifier: doi:10.1214/aos/1176345690
Project Euclid: euclid.aos/1176345690
[87] Morris, C. (1983). Natural exponential families with quadratic variance functions: Statistical theory. Ann. Statist. 11 515–589.
Mathematical Reviews (MathSciNet): MR696064
Zentralblatt MATH: 0521.62014
Digital Object Identifier: doi:10.1214/aos/1176346158
Project Euclid: euclid.aos/1176346158
[88] Newman, M. and Barkema, G. (1999). Monte Carlo Methods in Statistical Physics. Oxford Univ. Press.
Mathematical Reviews (MathSciNet): MR1691513
Zentralblatt MATH: 1012.82019
[89] Pitt, M. and Walker, S. (2006). Extended constructions of stationary autoregressive processes. Statist. Probab. Lett. 76 1219–1224.
Mathematical Reviews (MathSciNet): MR2269348
[90] Pitt, M. and Walker, S. (2005). Constructing stationary time series models using auxiliary variables with applications. J. Amer. Statist. Assoc. 100 554–564.
Mathematical Reviews (MathSciNet): MR2160559
Zentralblatt MATH: 1117.62412
Digital Object Identifier: doi:10.1198/016214504000001970
[91] Pitt, M., Chatfield, C. and Walker, S. (2002). Constructing first order stationary autoregressive models via latent processes. Scand. J. Statist. 29 657–663.
Mathematical Reviews (MathSciNet): MR1988417
Digital Object Identifier: doi:10.1111/1467-9469.00311
[92] Pommeret, D. (1996). Natural exponential families and Lie algebras. Exp. Math. 14 353–381.
Mathematical Reviews (MathSciNet): MR1418028
[93] Pommeret, D. (2001). Posterior variance for quadratic natural exponential families. Statist. Probab. Lett. 53 357–362.
Mathematical Reviews (MathSciNet): MR1856159
[94] Ringrose, J. (1971). Compact Non-Self-Adjoint Operators. Van Nostrand, New York.
[95] Rosenthal, J. (1995). Minorization conditions and convergence rates for Markov chain Monte Carlo. J. Amer. Statist. Assoc. 90 558–566.
Mathematical Reviews (MathSciNet): MR1340509
Zentralblatt MATH: 0824.60077
Digital Object Identifier: doi:10.2307/2291067
JSTOR: links.jstor.org
[96] Rosenthal, J. (1996). Analysis of the Gibbs sampler for a model related to James-Stein estimations. Statist. Comput. 6 269–275.
[97] Rosenthal, J. S. (2002). Quantitative convergence rates of Markov chains: A simple account. Electron. Comm. Probab. 7 123–128.
Mathematical Reviews (MathSciNet): MR1917546
Zentralblatt MATH: 1013.60053
[98] Roy, V. and Hobert, J. P. (2007). Convergence rates and asymptotic standard errors for MCMC algorithms for Bayesian probit regression. J. Roy. Statist. Soc. Ser. B 69 607–623.
Mathematical Reviews (MathSciNet): MR2370071
Digital Object Identifier: doi:10.1111/j.1467-9868.2007.00602.x
[99] Saloff-Coste, L. (2004). Total variation lower bounds for finite Markov chains: Wilson’s lemma. In Random Walks and Geometry (V. Kaimanovich and W. Woess, eds.) 515–532. de Gruyter, Berlin.
[100] Szego, G. (1959). Orthogonal Polynomials, rev. ed. Amer. Math. Soc., New York.
Mathematical Reviews (MathSciNet): MR106295
[101] Tanner, M. and Wong, W. (1987). The calculation of posterior distributions by data augmentation (with discussion). J. Amer. Statist. Assoc. 82 528–550.
Mathematical Reviews (MathSciNet): MR898357
Zentralblatt MATH: 0619.62029
Digital Object Identifier: doi:10.2307/2289457
JSTOR: links.jstor.org
[102] Tierney, L. (1994). Markov chains for exploring posterior distributions (with discussion). Ann. Statist. 22 1701–1762.
Mathematical Reviews (MathSciNet): MR1329166
Zentralblatt MATH: 0829.62080
Digital Object Identifier: doi:10.1214/aos/1176325750
Project Euclid: euclid.aos/1176325750
[103] Turcin, V. (1971). On the computation of multidimensional integrals by the Monte Carlo method. Probab. Appl. 16 720–724.
Mathematical Reviews (MathSciNet): MR292259
[104] Van Doorn, E. A. (2003). Birth-death processes and associated polynomials. In Proceedings of the Sixth International Symposium on Orthogonal Polynomials, Special Functions and their Applications (Rome, 2001). J. Comput. Appl. Math. 153 497–506.
Mathematical Reviews (MathSciNet): MR1985718
Zentralblatt MATH: 1039.60079
Digital Object Identifier: doi:10.1016/S0377-0427(02)00594-0
[105] Walter, G. and Hamedani, G. (1991). Bayes empirical Bayes estimation for natural exponential families with quadratic variance functions. Ann. Statist. 19 1191–1224.
Mathematical Reviews (MathSciNet): MR1126321
Zentralblatt MATH: 0741.62006
Digital Object Identifier: doi:10.1214/aos/1176348245
Project Euclid: euclid.aos/1176348245
[106] Wilson, D. (2004). Mixing times of Lozenge tiling and card shuffling Markov chains. Ann. Appl. Probab. 14 274–325.
Mathematical Reviews (MathSciNet): MR2023023
Zentralblatt MATH: 1040.60063
Digital Object Identifier: doi:10.1214/aoap/1075828054
Project Euclid: euclid.aoap/1075828054
[107] Yuen, W. K. (2000). Applications of geometric bounds to the convergence rate of Markov chains in ℝn. Stochastic Process. Appl. 87 1–23.
Mathematical Reviews (MathSciNet): MR1751167
Zentralblatt MATH: 1045.60102
Digital Object Identifier: doi:10.1016/S0304-4149(99)00113-1