Advances in Stochastic Simulation Methods / Edition 1

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This book presents 22 carefully edited chapters providing an up-to-dat e survey of new results and trends in the important areas of statistic al modeling, experimental design, and related issues of mathematical s tatistics and computational mathematics. The book shows the connection s between different trends of fundamental research and presents new al gorithms and models on this basis. The chapters are thematically organ ized into four parts: Simulation Models, Experimental Designs, Statist ical inference, Applied Statistics and Related Topics.

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Product Details

  • ISBN-13: 9780817641078
  • Publisher: Birkhauser Verlag
  • Publication date: 5/31/2001
  • Series: Statistics for Industry and Technology Series
  • Edition description: 2000
  • Edition number: 1
  • Pages: 386
  • Product dimensions: 10.00 (w) x 7.00 (h) x 0.94 (d)

Table of Contents

List of Tables
List of Figures
Pt. I Simulation Models
1 Solving the Nonlinear Algebraic Equations with Monte Carlo Method 3
2 Monte Carlo Algorithms For Neumann Boundary Value Problem Using Fredholm Representation 17
3 Estimation Errors for Functionals on Measure Spaces 29
4 The Multilevel Method of Dependent Tests 47
5 Algebraic Modelling and Performance Evaluation of Acyclic Fork-Join Queueing Networks 63
Pt. II Experimental Designs
6 Analytical Theory of E-Optimal Designs for Polynomial Regression 85
7 Bias Constrained Minimax Robust Designs for Misspecified Regression Models 117
8 A Comparative Study of MV - and SMV-Optimal Designs for Binary Response Models 135
9 On the Criteria for Experimental Design in Nonlinear Error-In-Variables Models 153
10 On Generating and Classifying all a[superscript n-m-1] Regularly Blocked Factional Designs 165
11 Locally Optimal Designs in Non-Linear Regression: A Case Study of the Michaelis-Menten Function 177
12 D-Optimal Designs for Quadratic Regression Models 189
13 On the Use of Symmetry in Optimal Design of Experiments 197
Pt. III Statistical Inference
14 Higher Order Moments of Order Statistics from the Pareto Distribution and Edgeworth Approximate Inference 207
15 Higher Order Moments of Order Statistics from the Power Function Distribution and Edgeworth Approximate Inference 245
16 Selecting from Normal Populations the One with the Largest Absolute Mean: Comon Unknown Variance Case 283
17 Conditional Inference for the Parameters of Pareto Distributions when Observed Samples are Progressively Censored 293
Pt. IV Applied Statistics and Related Topics
18 On Randomizing Estimators in Linear Regression Models 305
19 Nonstationary Generalized Automata with Periodically Variable Parameters and Their Optimization 315
20 Power of Some Asymptotic Tests for Maximum Entropy 337
21 Partially Inversion of Functions for Statistical Modelling of Regulatory Systems 355
22 Simple Efficient Estimation for Three-Parameter Lognormal Distributions with Applications to Emissions Data and State Traffic Rate Data 373
Subject Index 385
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