Professor Puri is one of the most versatile
and prolific
researchers in the world in mathematical
statistics. His research
areas include nonparametric statistics, order
statistics, limit
theory under mixing, time series, splines,
tests of normality,
generalized inverses of matrices and related
topics, stochastic
processes, statistics of directional data,
random sets, and fuzzy
sets and fuzzy measures. His fundamental
contributions in
developing new rank-based methods and precise
evaluation of the
standard procedures, asymptotic expansions
of distributions of
rank statistics, as well as large deviation
results concerning
them, span such areas as analysis of variance,
analysis of
covariance, multivariate analysis, and time
series, to mention a
few. His in-depth analysis has resulted in
pioneering research
contributions to prominent journals that
have substantial impact
on current research.
This book together with the other two volumes
(Volume 2:
Probability Theory and Extreme Value Theory;
Volume 3: Time
Series, Fuzzy Analysis and Miscellaneous
Topics), are a concerted
effort to make his research works easily
available to the
research community. The sheer volume of the
research output by
him and his collaborators, coupled with the
broad spectrum of the
subject matters investigated, and the great
number of outlets
where the papers were published, attach special
significance in
making these works easily accessible.
The papers selected for inclusion in this
work have been
classified into three volumes each consisting
of several parts.
All three volumes carry a final part consisting
of the contents
of the other two, as well as the complete
list of Professor
Puri's publications.
Contents
http://www.vsppub.com//books/mathe/cbk-MadLalPurSelColWorVol3TimSerFu.html
2003; xiv+788 pages
Set: Volumes 1 -- 3
ISBN 90-6764-387-4
Inverse and Ill-Posed Problems Series
2003; xii+216 pages
ISBN 90-6764-383-1
Contents:
http://www.vsppub.com///books/mathe/cbk-LinSobTypEquDegSemOpe.html
One of the aims of this book is to explain
in a basic manner
the seemingly difficult issues of mathematical
structure using
some specific examples as a guide. In each
of the cases
considered, a comprehensible physical problem
is approached, to
which the corresponding mathematical scheme
is applied, its
usefulness being duly demonstrated. The authors
try to fill the
gap that always exists between the physics
of quantum field
theories and the mathematical methods best
suited for its
formulation, which are increasingly demanding
on the mathematical
ability of the physicist.
Contents:
Survey of Path Integral Quantization and
Regularization
Techniques
Zeta-Function Regularization Method
Generalized Quadratic Spectra and Spectral
Functions on Non-Commutative
Spaces
Spectral Functions of Laplace Operator on
Locally Symmetric
Spaces of Rank One
Spinor Field
Spinor Fields and the Index Theorem
Field Fluctuations and Related Variances
The Multiplicative Anomaly
Some Applications of the Multiplicative Anomaly
The Casimir Effect
Readership: Mathematical and high energy
physicists.
370pp (approx.) Pub. date: Scheduled Winter
2003
ISBN 981-238-364-6
World Scientific Series on Nonlinear Science
Series, vol.46.
The main goal of this book is to prove analytically
and validate
experimentally that synchronization in multi-composed
mechanical
systems can be achieved in the case of partial
knowledge of the
state vector of the systems, i.e. when only
positions are
measured. For this purpose, synchronization
schemes based on
interconnections between the systems, feedback
controllers and
observers are proposed.
Because mechanical systems include a large
variety of systems,
and since it is impossible to address all
of them, the book
focuses on robot manipulators. Nonetheless
the ideas developed
here can be extended to other mechanical
systems, such as mobile
robots, motors and generators.
Contents:
Preliminaries
External Synchronization of Rigid Joint Robots
External Synchronization of Flexible Joint
Robots
Mutual Synchronization of Rigid Joint Robots
Experimental Case Study
Extensions
Readership: Students and researchers in mechanical
engineering
and control theory.
220pp (approx.) Pub. date: Scheduled Winter
2003
ISBN 981-238-605-X
0-534-38775-6
500 pages Case Bound 7 3/8 x 9 ?
Guided by problems that frequently arise
in actual practice,
James Higgins’ book presents a wide array
of nonparametric
methods of data analysis that researchers
will find useful. It
discusses a variety of nonparametric methods
and, wherever
possible, stresses the connection between
methods. For instance,
rank tests are introduced as special cases
of permutation tests
applied to ranks. The author provides coverage
of topics not
often found in nonparametric textbooks, including
procedures for
multivariate data, multiple regression, multi-factor
analysis of
variance, survival data, and curve smoothing.
This truly modern
approach teaches non-majors how to analyze
and interpret data
with nonparametric procedures using today’s
computing
technology.
ames J. Higgins
James J. Higgins is Professor of Statistics
at Kansas State
University and Fellow of the American Statistical
Association. He
is the co-author of the Duxbury textbook
“Concepts in
Probability and Stochastic Modeling” with
Sallie Keller-McNulty
and has over 80 scientific publications to
his credit. He is a
statistical consultant for Kansas State Research
and Extension.
His research interests include nonparametric
statistics and
reliability theory.
Table of Contents
1. ONE-SAMPLE METHODS.
Preliminaries. A Nonparametric Test and Confidence
Interval for
the Median. Estimating the Population CDF
and Quantiles. A
Comparison of Statistical Tests.
2. TWO-SAMPLE METHODS.
A Two-Sample Permutation Test. Permutation
Tests Based on the
Median and Trimmed Means. Random Sampling
the Permutations.
Wilcoxon Rank-Sum Test. Wilcoxon Rank-Sum
Test Adjusted for Ties.
Mann-Whitney Test and a Confidence Interval.
Scoring Systems.
Test for Equality of Scale Parameters and
an Omnibus Test.
Selecting Among Two-Sample Tests. Large Sample
Approximations.
Exercises.
3. K-SAMPLE METHODS.
K-Sample Permutation Tests. The Kruskal-Wallis
Test. Multiple
Comparisons. Ordered Alternatives. Exercises.
4. PAIRED COMPARISONS AND BLOCKED DESIGNS.
Paired Comparison Permutation Test. Signed-Rank
Test. Other
Paired-Comparison Tests. A Permutation Test
for a Randomized
Complete Block Design. Friedman!|s Test for
a Randomized Complete
Block Design. Ordered Alternatives for a
Randomized Complete
Block Design. Exercises.
5. TESTS FOR TRENDS AND ASSOCIATION.
A Permutation Test for Correlation and Slope.
Spearman Rank
Correlation. Kendall!|s Tau. Permutation
Tests for Contingency
Tables. Fisher!|s Exact Test for a 2 ?e 2
Contingency Table.
Contingency Tables With Ordered Categories.
Mantel-Haenszel Test.
Exercises.
6. MULTIVARIATE TESTS.
Two-Sample Multivariate Permutation Tests.
Two-Sample
Multivariate Rank Tests. Multivariate Paired
Comparisons.
Multivariate Rank Tests for Paired Comparisons.
Multi-response
Categorical Data. Exercises.
7. ANALYSIS OF CENSORED DATA.
Estimating the Survival Function. Permutation
Tests for Two-Sample
Censored Data. Gehan!|s Generalization of
the Mann-Whitney-Wilcoxon
Test. Scoring Systems for Censored Data.
Tests Using Scoring
Systems for Censored Data. Exercises.
8. NONPARAMETRIC BOOTSTRAP METHODS.
The Basic Bootstrap Method. Bootstrap Intervals
for Location-Scale
Models. BCA and Other Bootstrap Intervals.
Correlation and
Regression. Two-Sample Inference. Bootstrap
Sampling from Several
Populations. Bootstrap Sampling for Multiple
Regression.
Multivariate Bootstrap Sampling. Exercises.
9. MULTIFACTOR EXPERIMENTS.
Analysis of Variance Models. Aligned Rank
Transform. Testing for
Lattice-Ordered Alternatives. Exercises.
10. SMOOTHING METHODS AND ROBUST MODEL FITTING.
Estimating the Probability Density Function.
Nonparametric Curve
Smoothing. Robust and Rank-Based Regression.
Exercises.
TABLES.
REFERENCES.