Hisashi Tanizaki / Kobe University, Kobe, Japan

Computational Methods in Statistics and Econometrics

Statistics: Textbooks and Monographs series, Volume: 172

Published: 01/01/2004
Hard Cover
480 pages | Illustrated
Print ISBN: 0-8247-4804-2

Description


Reflecting current technological capacities and analytical trends, Computational Methods in Statistics and Econometrics showcases Monte Carlo and nonparametric statistical methods for models, simulations, analyses, and interpretations of statistical and econometric data?benefiting from straightforward explanations of mathematical concepts, hundreds of figures and tables, and a range of empirical examples.

Explores applications of Monte Carlo methods in Bayesian estimation, state space modeling, and bias correction of ordinary least squares in autoregressive models.

Accompanied by a CD-ROM displaying all source codes used in the text, Computational Methods in Statistics and Econometrics

offers a comprehensive review of introductory notions in statistics such as variable transformation, statistical inference, hypothesis testing, and regression analysis

authoritatively illuminates the fundamental topic of uniform random number generation

demonstrates the generation of diverse continuous- and discrete-type random draws, from gamma, t, and F to Bernoulli and binomial distributions

explains the inverse transform method for use with Laplace, Cauchy, and other distributions

details random draw approaches for multivariate distributions

describes random number generation via importance and rejection sampling methods and the Metropolis-Hastings algorithm

outlines nonparametric methods for finding the difference between two sample means, including logistic and Cauchy score tests and Fisherfs randomization test

compares power and asymptotic relative efficacy of results obtained through nonparametric tests versus the t test

considers Monte Carlo and nonparametric methods for testing correlation and regression coefficients and establishing the independence of two samples

Table of Contents

Elements of Statistics
Monte Carlo Statistical Methods
Random Number Generation I
Random Number Generation II
Selected Applications of Monte Carlo Methods
Bayesian Estimation
Bias Correction of OLSE in AE Models
State Space Modeling
Nonparametric Statistical Methods
Difference Between Two-Sample Means
Independence Between Two Samples
Source Code Index
Index.

Edited by: Nitis Mukhopadhyay/Sujay Datta/ Saibal Chattopadhyay

Applied Sequential Methodologies
Real-World Examples with Data Analysis

Statistics: Textbooks and Monographs series, Volume: 173

02/01/2004
Hard Cover
418 pages | Illustrated
Print ISBN: 0-8247-5395-X

Description

A technically precise yet clear presentation of modern sequential methodologies having immediate applicability to practical problems in the real world. Articles contain valuable methods for data mining, agriculture science, genetics, computer simulation, finance, clinical trials, psychology, and numerous additional areas of application.

Table of Contents

Passive Acoustic Detection of Marine Mammals Using Pagefs Test
Douglas A. Abraham
Two-Stage Procedures for Selecting the Best Component of a Multivariate Distribution
Makoto Aoshima, Mitsuru Aoki, and Masaki Kai
Sequential Randomization Tests
Tathagata Banerjee and Onkar Prosad Ghosh
Sequential Methods for Multistate Processes
Michael I. Baron
Sequential Adaptive Designs for Clinical Trials with Longitudinal Responses
Atanu Biswas and Anup Dewanji
Sequential Approaches to Data Mining
Yuan-Chin Ivan Chang and Adam Martinsek
Approximations and Bounds for Moving Sums of Discrete Random Variables
Jie Chen and Joseph Glaz
Estimation of the Slope in a Measurement-Error Model
Sujay Datta and Saibal Chattopadhyay
Kernel Density Estimation of Wool Fiber Diameter
Basil M. de Silva and Nitis Mukhopadhyay
Financial Applications of Sequential Nonparametric Curve Estimation
Sam Efromovich

Alan C. Krinik / Randall J. Swift

Stochastic Processes and Functional Analysis: Recent Advances

Lecture Notes In Pure and Applied Mathematics, Volume 238

02/01/2004
Hard Cover
400 pages | Illustrated
Print ISBN: 0-8247-5404-2

Description

An expansion on the recent American Mathematical Society Special Session celebrating M. M. Raofs distinguished career, this extraordinary compilation includes most of the presented papers as well as ancillary contributions from session invitees. This book decisively shows the effectiveness of abstract analysis for solving fundamental problems of stochastic theory?specifically the use of functional analytic methods for elucidating stochastic processes, as made manifest in Raofs prolific achievements.

Table of Contents

Applications of Sinkhorn Balancing: The Monomer-Dimer Problem
I. Beichl and F. Sullivan
Zakai Equation of Nonlinear Filtering with Ornstein-Uhlenbeck Noise: Existance and Uniqueness
A. Bhatt and B. Rajput
Hyperfunctionals and Generalized Distributions
M Burgin
Process-Measures and their Stochastic Integral
N. Dinculeanu
Invariant Sets for Nonlinear Operators
J. Goldstein
The Immigrant-Emigration with Catastrophe Model
M. Green
Approximating Scale Mixtures
H. Hamdan and J. Nolan
Cylcostationary Arrays: Their Unitary Operators and Representations
H. Hurd and T. Koski
Pseudoergodicity in Information Channels
Y. Kakihara
Operator Theoretic Review for Information Channels
Y. Kakihara
Connections Between Birth-Death Processes
A.C. Krinik and G. Rubino
Integrated Gaussian Processes and their Reproducing Kernel Hilbert Spaces
M. Lukic
Moving Average Representation and Prediction for Multidimensional Harmonizable Processes
M. H. Mehlman
Double-Level Averaging on a Stratified Space
N. OfBryant
The Problem of Optimal Asset Allocation with Stable Distributed Returns
S. Rachev, S. Ortobelli, and E. Schwartz


W. J. Wickless / The University of Connecticut at Storrs, U.S.A.

A First Graduate Course in Abstract Algebra

Pure and Applied Mathematics, Volume 266

02/01/2004
Hard Cover
250 pages | Illustrated
Print ISBN: 0-8247-5627-4

Description

Realizing the specific needs of first-year graduate students, this reference allows readers to grasp and master fundamental concepts in abstract algebra?establishing a clear understanding of basic linear algebra and number, group, and commutative ring theory and progressing to sophisticated discussions on Galois and Sylow theory, the structure of abelian groups, the Jordan canonical form, and linear transformations and their matrix representations.

Table of Contents

Groups (Mostly Finite)
Rings (Mostly Domains)
Modules
Vector Spaces
Fields and Galois Theory
Topics in Noncommutative Rings
Group Extensions
Topics in Abelian Groups
References
Index