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Advances in Stochastic Simulation Methods

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

08.10.2012

Herausgeber

N. Balakrishnan + weitere

Verlag

Birkhäuser Boston

Seitenzahl

386

Maße (L/B/H)

25,4/17,8/2,3 cm

Gewicht

798 g

Auflage

Softcover reprint of the original 1st ed. 2000

Sprache

Englisch

ISBN

978-1-4612-7091-1

Beschreibung

Portrait

N. Balakrishnan is an Associate Director and Professor at Department of Aerospace Engineering and Supercomputer Edu- cation and Research Centre, Indian Institute of Science. His research interests include numerical electromagnetic, multi-parameter radars, and signal processing. His publications include 19 books and many peer-reviewed journal papers.

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

08.10.2012

Herausgeber

Verlag

Birkhäuser Boston

Seitenzahl

386

Maße (L/B/H)

25,4/17,8/2,3 cm

Gewicht

798 g

Auflage

Softcover reprint of the original 1st ed. 2000

Sprache

Englisch

ISBN

978-1-4612-7091-1

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: GPSR Kontakt

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  • Produktbild: Advances in Stochastic Simulation Methods
  • Produktbild: Advances in Stochastic Simulation Methods
  • I: Simulation Models.- 1 Solving the Nonlinear Algebraic Equations with Monte Carlo Method.- 2 Monte Carlo Algorithms For Neumann Boundary Value Problem Using Fredholm Representation.- 3 Estimation Errors for Functionals on Measure Spaces.- 4 The Multilevel Method of Dependent Tests.- 5 Algebraic Modelling and Performance Evaluation of Acyclic Fork-Join Queueing Networks.- II: Experimental Designs.- 6 Analytical Theory of E-Optimal Designs for Polynomial Regression.- 7 Bias Constrained Minimax Robust Designs for Misspecified Regression Models.- 8 A Comparative Study of MV- and SMV-Optimal Designs for Binary Response Models.- 9 On the Criteria for Experimental Design in Nonlinear Error-In-Variables Models.- 10 On Generating and Classifying all q71-m-1Regularly Blocked Factional Designs.- 11 Locally Optimal Designs in Non-Linear Regression: A Case Study of the Michaelis-Menten Function.- 12 D-Optimal Designs for Quadratic Regression Models.- 13 On the Use of Symmetry in Optimal Design of Experiments.- III: Statistical Inference.- 14 Higher Order Moments of Order Statistics from the Pareto Distribution and Edgeworth Approximate Inference.- 15 Higher Order Moments of Order Statistics from the Power Function Distribution and Edgeworth Approximate Inference.- 16 Selecting from Normal Populations the One with the Largest Absolute Mean: Comon Unknown Variance Case.- 17 Conditional Inference for the Parameters of Pareto Distributions when Observed Samples are Progressively Censored.- IV: Applied Statistics and Related Topics.- 18 On Randomizing Estimators in Linear Regression Models.- 19 Nonstationary Generalized Automata with Periodically Variable Parameters and Their Optimization.- 20 Power of Some Asymptotic Tests for Maximum Entropy.- 21 Partially Inversion of Functions for Statistical Modelling of Regulatory Systems.- 22 Simple Efficient Estimation for Three-Parameter Lognormal Distributions with pplications to Emissions Data and State Traffic Rate Data.