Discrete Distributions in Engineering and the Applied Sciences

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This is an introductory book on discrete statistical distributions and its applications. It discusses only those that are widely used in the applications of probability and statistics in everyday life. The purpose is to give a self-contained introduction to classical discrete distributions in statistics. Instead of compiling the important formulas (which are available in many other textbooks), we focus on important applications of each distribution in various applied fields like bioinformatics, genomics, ecology, electronics, epidemiology, management, reliability, etc., making this book an indispensable resource for researchers and practitioners in several scientific fields. Examples are drawn from different fields. An up-to-date reference appears at the end of the book.

Chapter 1 introduces the basic concepts on random variables, and gives a simple method to find the mean deviation (MD) of discrete distributions. The Bernoulli and binomial distributions are discussed in detail in Chapter 2. A short chapter on discrete uniform distribution appears next. The next two chapters are on geometric and negative binomial distributions. Chapter 6 discusses the Poisson distribution in-depth, including applications in various fields. Chapter 7 is on hypergeometric distribution. As most textbooks in the market either do not discuss, or contain only brief description of the negative hypergeometric distribution, we have included an entire chapter on it. A short chapter on logarithmic series distribution follows it, in which a theorem to find the kth moment of logarithmic distribution using (k-1)th moment of zero-truncated geometric distribution is presented. The last chapter is on multinomial distribution and its applications.

The primary users of this book are professionals and practitioners in various fields of engineering and the applied sciences. It will also be of use to graduate students in statistics, research scholars in science disciplines, and teachers of statistics, biostatistics, biotechnology, education, and psychology.

Author(s): Rajan Chattamvelli, Ramalingam Shanmugam
Series: Synthesis Lectures on Information Concepts, Retrieval, and Services
Publisher: Morgan & Claypool Publishers
Year: 2020

Language: English
Pages: 227

List of Figures
List of Tables
Glossary
Discrete Random Variables
Introduction
Discrete Models
Uses of Discrete Probabilistic Models
Discrete Random Variables
Conditional Models
Linear Combination of Random Variables
Random Sums of Random Variables
Mixed Random Variables
Displaced Random Variables
Domain of a Random Variable
CDF and SF
Properties of CDF
Binomial Theorem
Recurrence Relation for Binomial Coefficients
Distributions Obtainable from Binomial Theorem
Mean Deviation of Discrete Distributions
New Measures of Variability
A New Family of Distributions
Truncated Models
Zero-Inflated Distributions
Hurdle Models
Power Series Distributions
Summary
Binomial Distribution
Introduction
Bernoulli Trials
``Success'' Demystified
Spatial Processes
Dichotomization Using Cutoff
Bernoulli Distribution
Basic Properties of Bernoulli Distribution
Related Distributions
Random Numbers
Binomial Distribution
Dependent Trials
Properties of Binomial Distribution
Moments
Moment Recurrences
Additivity Property
MD of Binomial Distribution
New Distribution from MD
Tests of Hypothesis
Binomial Confidence Intervals
Generating Functions
Probability Generating Functions
Variance Generating Function (VGF)
Algorithm for Computing Binomial Distribution
Tail Probabilities
Approximations
Limiting Form of Binomial Distribution
Special Binomial Distributions
Distribution of U = |X-Y|/2
Truncated Binomial Distributions
Inflated Binomial Distributions
Log-Binomial Distribution
Applications
Microbiology
Epidemiology
Genetics
Reliability
K-out-of-n System Operation
K-out-of-n Detection
Ensemble Methods
SQC
Electronics
Summary
Discrete Uniform Distribution
Introduction
Discrete Uniform Distribution
Mean and Variance
Properties of Discrete Uniform Distribution
Special Symmetry
Relation to Other Distributions
Applications
Sampling
Random Numbers
Summary
Geometric Distribution
Derivation
Alternate Forms
Relation to Other Distributions
Properties of Geometric Distribution
CDF and SF
Tail Probabilities
Distribution of Extremes
Memory-Less Property
Moments and Generating Functions
Special Geometric Distributions
Arithmetico-Geometric Distribution
Log-Geometric Distributions
Truncated Geometric Distributions
Zero-Inflated Geometric Distribution
Random Samples
Applications
Manufacturing
Machine Failures
Medical Imaging
Transportation
Summary
Negative Binomial Distribution
Derivation
Alternate Forms
Relation to Other Distributions
Properties of NBINO(k, p)
MGF of Negative Binomial Distribution
Moments of Negative Binomial Distribution
Variance Generating Function
Factorial Moments
Poisson Approximation
Derivation Using PGF
Moment Recurrence
Tail Probabilities
Truncated Negative Binomial Distributions
Zero-Inflated Negative Binomial (ZINB) Models
Generalizations
Applications
Power Restoration Modeling
Capture-Mark-Recapture Model
Medical Sciences
Summary
Poisson Distribution
Introduction
Importance of Counts
Probability Mass Function
Dilution Techniques
Moment Approximation
Derivation of Poisson Law
Properties of Poisson Distribution
Moments and MGF
Factorial Moments
Moment Generating Function
Additivity Property
Relation to Other Distributions
Algorithms for Poisson Distribution
Approximations
Generalized Poisson Distributions
Intervened Poisson Distribution (IPD)
Spinned Poisson Distribution (SPD)
Poisson Process
Fitting a Poisson Distribution
Truncated Poisson Distribution
Zero-Inflated Poisson Distribution
Double Poisson Distribution
Applications
Healthcare
Electronics
Poisson Regression
Management Sciences
Quantum Cryptography
Poisson Heterogeneity Test
Summary
Hypergeometric Distribution
Introduction
Alternate Forms
Relation to Other Distributions
Properties of Hypergeometric Distribution
Factorial Moments of Hypergeometric Distribution
Mean and Variance of Hypergeometric Distribution
Generating Functions
Mean Deviation
Truncated Hypergeometric Distributions
Approximations for Hypergeometric Distribution
Applications
Hypergeometric Tests
Fisher's Exact Test
Median Test
Runs Test
Acceptance Sampling
The CMR Model
Line-Transect Model
Highway Engineering
Medical Sciences
Bioinformatics
Summary
Negative Hypergeometric Distribution
Derivation
Dual NHGD
Alternate Forms
Relation to Other Distributions
Properties of NHGD
Generating Functions
Mean and Variance
Factorial Moments
Beta-Binomial Distribution
Mean and Variance
Mean Deviation
Truncated NHGD
Applications
Computer Games
CMR Estimation
Industrial Quality Control
Summary
Logarithmic Series Distribution
Introduction
Alternate Forms
Relation to Other Distributions
Properties of Logarithmic Distribution
Mean and Variance
Factorial Moments
CDF and SF
Generating Functions
Zero-Inflated Logarithmic Distribution
Lagrangian Logarithmic Distribution
Applications
Scientific Research
Ecology
Finance
Summary
Multinomial Distribution
Introduction
Alternate Forms
Relation to Other Distributions
Properties of Multinomial Distribution
Marginal Distributions
Conditional Distributions
Generating Functions
Moments and Cumulants
Applications
Contingency Tables
Genomics
Finance
Reliability
Summary
Bibliography
Authors' Biographies
Index
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