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Computational Probability Applications

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Cover of 'Computational Probability Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Accurate Estimation with One Order Statistic
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    Chapter 2 On the Inverse Gamma as a Survival Distribution
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    Chapter 3 Order Statistics in Goodness-of-Fit Testing
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    Chapter 4 The “Straightforward” Nature of Arrival Rate Estimation?
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    Chapter 5 Survival Distributions Based on the Incomplete Gamma Function Ratio
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    Chapter 6 An Inference Methodology for Life Tests with Full Samples or Type II Right Censoring
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    Chapter 7 Maximum Likelihood Estimation Using Probability Density Functions of Order Statistics
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    Chapter 8 Notes on Rank Statistics
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    Chapter 9 Control Chart Constants for Non-normal Sampling
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    Chapter 10 Linear Approximations of Probability Density Functions
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    Chapter 11 Univariate Probability Distributions
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    Chapter 12 Moment-Ratio Diagrams for Univariate Distributions
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    Chapter 13 The Distribution of the Kolmogorov–Smirnov, Cramer–von Mises, and Anderson–Darling Test Statistics for Exponential Populations with Estimated Parameters
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    Chapter 14 Parametric Model Discrimination for Heavily Censored Survival Data
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    Chapter 15 Lower Confidence Bounds for System Reliability from Binary Failure Data Using Bootstrapping
Attention for Chapter 9: Control Chart Constants for Non-normal Sampling
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Chapter title
Control Chart Constants for Non-normal Sampling
Chapter number 9
Book title
Computational Probability Applications
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-43317-2_9
Book ISBNs
978-3-31-943315-8, 978-3-31-943317-2
Authors

William H. Kaczynski, Lawrence M. Leemis

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