A Festschrift for Herman Rubin
Editor: Anirban DasGupta
Lecture Notes--Monograph Series, Volume 45
Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2004.
417 pp.
Abstract:
This volume is a collection of 32 original papers and two biographical accounts put together as a Festschrift to Herman Rubin to honor his diverse and many deep contributions to mathematical sciences over more than 50 years. The topics of the original articles touch on the main themes in which Professor Rubin has contributed, as well as other topics of intense current activity. This volume contains innovative new methodological articles on cluster analysis, goodness of fit, likelihood inference, classification algorithms, and meta analysis. On the purely theoretical side, there are a number of comprehensive review articles on fractional Brownian motion, stochastic integration, de Finetti theorems, admissibility, and estimation under constraints. Each of these review articles provides readable glimpses into the current state of the art. Some notable classic unsolved problems in number theory and random permutations provide attractive additions to the interesting landscape of this volume.
Subjects:
Mathematical statisticsBayesian statistical decision theory
Estimation theory
Set theory
Probabilities
62-06 (primary)
00A30 (secondary)
ISBN:0-940600-61-7
Mathmatical Reviews number (MathSciNet): MR2126881
Zentralblatt Math Identifier: 1066.62002
Copyright © 2004, Institute of Mathematical Statistics.
Title and Copyright Pages
Evaluating improper priors and the recurrence of symmetric Markov chains: an overview
Morris L. Eaton; 5-20
Estimation in restricted parameter spaces: a review
Eric Marchand, and William E. Strawderman; 21-44
A Rubinesque theory of decision
J. B. Kadane, Mark J. Schervish, and Teddy Seidenfeld; 45-55
On the distribution of the greatest common divisor
Persi Diaconis, and Paul Erdös; 56-61
Versions of de Finetti’s Theorem with applications to damage models
C. R. Rao, and D. N. Shanbhag; 62-74
A short history of stochastic integration and mathematical finance: the early years, 1880–1970
Robert Jarrow, and Philip Protter; 75-91
Non-linear filtering with Gaussian martingale noise: Kalman filter with fBm noise
L. Gawarecki, and V. Mandrekar; 92-97
Self-similar processes, fractional Brownian motion and statistical inference
B. L. S. Prakasa Rao; 98-125
Some properties of the arc-sine law related to its invariance under a family of rational maps
Jim Pitman, and Marc Yor; 126-137
On time changing continuous martingales to Brownian motion
Burgess Davis; 138-139
On counts of Bernoulli strings and connections to rank orders and random permutations
Jayaram Sethuraman, and Sunder Sethuraman; 140-152
Chebyshev polynomials and $G$-distributed functions of $F$-distributed variables
Anirban DasGupta, and L. Shepp; 153-163
Zeroes of infinitely differentiable characteristic functions
Herman Rubin, and Thomas M. Sellke; 164-170
On the characteristic function of Pearson type IV distributions
Wei-Liem Loh; 171-179
Characterizations, Sub and resampling, and goodness of fit
L. Brown, Anirban DasGupta, John Marden, and Dimitris Politis; 180-206
Combining correlated unbiased estimators of the mean of a normal distribution
Timothy Keller, and Ingram Olkin; 218-227
An asymptotic minimax determination of the initial sample size in a two-stage sequential procedure
Michael Woodroofe; 228-236
Estimating gradient trees
Ming-Yen Cheng, Peter Hall, and John A. Hartigan; 237-249
Conservative bounds on extreme P-values for testing the equality of two probabilities based on very large sample sizes
Herman Chernoff; 250-254
Detecting a target in very noisy data from multiple looks
Jiashun Jin; 255-286
$r$-scan extremal statistics of inhomogeneous Poisson processes
Samuel Karlin, and Chingfer Chen; 287-290
On the strong consistency, weak limits and practical performance of the ML estimate and Bayesian estimates of a symmetric domain in $R^k$
Wen-Chi Tsai, and Anirban DasGupta; 291-308
Maximum likelihood estimation for the contact process
Marta Fiocco, and Willem R. van Zwet; 309-318
On the "Poisson boundaries" of the family of weighted Kolmogorov statistics
Leah Jager, and Jon A. Wellner; 319-331
A theorem on compatibility of systems of sets with applications
A. Goswami, and B. V. Rao; 332-336
Generalized Accept-Reject sampling schemes
George Casella, Christian P. Robert, and Martin T. Wells; 342-347
Scalable mining for classification rules in relational databases
Min Wang, Bala Iyer, and Jeffrey Scott Vitter; 348-377
Forecasting NBA basketball playoff outcomes using the weighted likelihood
Feifang Hu, and James V. Zidek; 385-395
Distributions of failure times associated with non-homogeneous compound Poisson damage processes
S. Zacks; 396-407
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