Sequential Methods and Their Applications
Interactively Run Simulations and Experiment with Real or Simulated Data to Make Sequential Analysis Come AliveTaking an accessible, nonmathematical approach to this field, Sequential Methods and Their Applications illustrates the efficiency of sequential methodologies when dealing with contemporary statistical challenges in many areas.The book fir
1133036737
Sequential Methods and Their Applications
Interactively Run Simulations and Experiment with Real or Simulated Data to Make Sequential Analysis Come AliveTaking an accessible, nonmathematical approach to this field, Sequential Methods and Their Applications illustrates the efficiency of sequential methodologies when dealing with contemporary statistical challenges in many areas.The book fir
84.99 In Stock
Sequential Methods and Their Applications

Sequential Methods and Their Applications

Sequential Methods and Their Applications

Sequential Methods and Their Applications

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$84.99 

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Overview

Interactively Run Simulations and Experiment with Real or Simulated Data to Make Sequential Analysis Come AliveTaking an accessible, nonmathematical approach to this field, Sequential Methods and Their Applications illustrates the efficiency of sequential methodologies when dealing with contemporary statistical challenges in many areas.The book fir

Product Details

ISBN-13: 9781040201152
Publisher: CRC Press
Publication date: 10/28/2008
Sold by: Barnes & Noble
Format: eBook
Pages: 504
File size: 9 MB

About the Author

Mukhopadhyay, Nitis; de Silva, Basil M.

Table of Contents

Preface. Objectives, Coverage, and Hopes. Why Sequential? Sequential Probability Ratio Test. Sequential Tests for Composite Hypotheses. Sequential Nonparametric Tests. Estimation of the Mean of a Normal Population. Location Estimation: Negative Exponential Distribution. Point Estimation of the Mean of an Exponential Population. Fixed-Width Intervals from MLEs. Distribution-Free Methods in Estimation. Multivariate Normal Mean Vector Estimation. Estimation in a Linear Model. Estimating the Difference of Two Normal Means. Selecting the Best Normal Population. Sequential Bayesian Estimation. Selected Applications. Appendix. References. Index.
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