Multivariate Statistics and Probability: Essays in Memory of Paruchuri R. Krishnaiah

Front Cover
C. R. Rao, M. M. Rao
Academic Press, May 10, 2014 - Mathematics - 582 pages
Multivariate Statistics and Probability: Essays in Memory of Paruchuri R. Krishnaiah is a collection of essays on multivariate statistics and probability in memory of Paruchuri R. Krishnaiah (1932-1987), who made significant contributions to the fields of multivariate statistical analysis and stochastic theory. The papers cover the main areas of multivariate statistical theory and its applications, as well as aspects of probability and stochastic analysis. Topics range from finite sampling and asymptotic results, including aspects of decision theory, Bayesian analysis, classical estimation, regression, and time-series problems. Comprised of 35 chapters, this book begins with a discussion on the joint asymptotic distribution of marginal quantiles and quantile functions in samples from a multivariate population. The reader is then introduced to kernel estimators of density function of directional data; moment conditions for valid formal edgeworth expansions; and ergodicity and central limit theorems for a class of Markov processes. Subsequent chapters focus on minimal complete classes of invariant tests for equality of normal covariance matrices and sphericity; normed likelihood as saddlepoint approximation; generalized Gaussian random fields; and smoothness properties of the conditional expectation in finitely additive white noise filtering. This monograph should be of considerable interest to researchers as well as to graduate students working in theoretical and applied statistics, multivariate analysis, and random processes.
 

Contents

In Memoriam
1
Chapter 1 Joint Asymptotic Distribution of Marginal Quantiles and Quantile Functions in Samples from a Multivariate Population
15
Chapter 2 Kernel Estimators of Density Function of Directional Data
24
Chapter 3 On Determination of the Order of an Autoregressive Model
40
Chapter 4 Admissible Linear Estimation in a General GaussMarkov Model with an Incorrectly Specified Dispersion Matrix
53
Chapter 5 On Moment Conditions for Valid Formal Edgeworth Expansions
68
Chapter 6 Ergodicity and Central Limit Theorems for a Class of Markov Processes
80
Chapter 7 Conditionally Ordered Distributions
91
Chapter 20 A Generalized CauchyBinet Formula and Applications to Total Positivity and Majorization
284
UnionIntersection Principle and Preliminary Test Versions
300
Chapter 22 Some Asymptotic Inferential Problems Connected with Elliptical Distributions
319
Chapter 23 Stochastic Integrals of EmpiricalType Processes with Applications to Censored Regression
334
Chapter 24 Nonminimum Phase NonGaussian Deconvolution
359
Chapter 25 Inference in a Model with at Most One SlopeChange Point
375
Chapter 26 Maximum Likelihood Principle and Model Selection when the True Model Is Unspecified
392
Chapter 27 An Asymptotic Minimax Theorem of Order n12
404

Chapter 8 A Discounted Cost Relationship
105
Chapter 9 Strong Consistency of MEstimates in Linear Models
116
Chapter 10 Minimal Complete Classes of Invariant Tests for Equality of Normal Covariance Matrices and Sphericity
131
Chapter 11 Invariance Principles for Changepoint Problems
151
Chapter 12 On the Area of the Circles Covered by a Random Walk
169
Chapter 13 Normed Likelihood as Saddlepoint Approximation
181
Chapter 14 Nonuniform Error Bounds for Asymptotic Expansions of Scale Mixtures of Distributions
194
Chapter 15 Empirical and Hierarchical Bayes Competitors of Preliminary Test Estimators in Two Sample Problems
206
Chapter 16 On Confidence Bands in Nonparametric Density Estimation and Regression
228
Chapter 17 A Note on Generalized Gaussian Random Fields
255
Chapter 18 Smoothness Properties of the Conditional Expectation in Finitely Additive White Noise Filtering
261
Chapter 19 Equivariant Estimation of a Mean Vector µ of Nµ with µ1µ1 or 12µc or σ2µµl
270
Chapter 28 An Improved Estimation Method for Univariate Autoregressive Models
422
Chapter 29 Paradoxes in Conditional Probability
434
Chapter 30 Inference Properties of a OneParameter Curved Exponential Family of Distributions with Given Marginals
447
Chapter 31 Asymptotically Precise Estimate of the Accuracy of Gaussian Approximation in Hubert Space
457
Chapter 32 The Estimation of the Bispectral Density Function and the Detection of Periodicities in a Signal
484
Chapter 33 Analysis of Odds Ratios in 2n Ordinal Contingency Tables
505
Chapter 34 Asymptotic Expansions of the Distributions of Some Test Statistics for Gaussian ARMA Processes
521
Chapter 35 Estimating Multiple Rater Agreement for a Rare Diagnosis
539
Author Index
563
Subject Index
565
Copyright

Other editions - View all

Common terms and phrases

About the author (2014)

Professor C. R. Rao, born in India, is one of this century's foremost statisticians, and received his education in statistics at the Indian Statistical Institute (ISI), Calcutta. He is Emeritus Holder of the Eberly Family Chair in Statistics at Penn State and Director of the Center for Multivariate Analysis. He has long been recognized as one of the world's top statisticians, and has been awarded 34 honorary doctorates from universities in 19 countries spanning 6 continents. His research has influenced not only statistics, but also the physical, social and natural sciences and engineering. In 2011 he was recipient of the Royal Statistical Society's Guy Medal in Gold which is awarded triennially to those "who are judged to have merited a signal mark of distinction by reason of their innovative contributions to the theory or application of statistics". It can be awarded both to fellows (members) of the Society and to non-fellows. Since its inception 120 years ago the Gold Medal has been awarded to 34 distinguished statisticians. The first medal was awarded to Charles Booth in 1892. Only two statisticians, H. Cramer (Norwegian) and J. Neyman (Polish), outside Great Britain were awarded the Gold medal and C. R. Rao is the first non-European and non-American to receive the award. Other awards he has received are the Gold Medal of Calcutta University, Wilks Medal of the American Statistical Association, Wilks Army Medal, Guy Medal in Silver of the Royal Statistical Society (UK), Megnadh Saha Medal and Srinivasa Ramanujan Medal of the Indian National Science Academy, J.C.Bose Gold Medal of Bose Institute and Mahalanobis Centenary Gold Medal of the Indian Science Congress, the Bhatnagar award of the Council of Scientific and Industrial Research, India and the Government of India honored him with the second highest civilian award, Padma Vibhushan, for “outstanding contributions to Science and Engineering / Statistics?, and also instituted a cash award in honor of C R Rao, “to be given once in two years to a young statistician for work done during the preceding 3 years in any field of statistics.For his outstanding achievements Rao has been honored with the establishment of an institute named after him, C.R.Rao Advanced Institute for Mathematics, Statistics and Computer Science, in the campus of the University of Hyderabad, India. C.R. Rao won International Statistics Prize in 2023. He passed away in 2023 two weeks before his 103rd birthday.

Bibliographic information