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Probability Distributions. With Truncated, Log and Bivariate Extensions

Nick T. Thomopoulos (Taschenbuch, Englisch)

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Beschreibung
This unique SpringerBrief presents statistical methods and tables not readily available in other publications.  It begins with a review of the commonly used continuous and discrete probability distributions. Several useful distributions that are not so common and less understood are described with examples and applications in full detail: discrete normal, left-partial, right-partial, left-truncated normal, right-truncated normal, lognormal, bivariate normal, and bivariate lognormal. Table values are provided with examples that enable researchers to easily apply the distributions to real applications and sample data. The left- and right-truncated normal distributions offer a wide variety of shapes in contrast to the symmetrically shaped normal distribution, and a newly developed spread ratio enables analysts to determine which of the three distributions best fits a particular set of sample data.
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Technische Daten


Erscheinungsdatum
01.01.2017
Sprache
Englisch
EAN
9783319519715
Herausgeber
Springer International Publishing
Autor
Nick T. Thomopoulos
Seitenanzahl
149
Einbandart
Taschenbuch
Inhaltsverzeichnis
1. Continuous Distributions1.1 Introduction1.2 Sample Data Statistics1.3 Notation1.4 Parameter Estimating Methods1.5 Transforming Variables Transform Data to (0,1) Transform Data to (x ≥0) 1.6 Continuous Random Variables1.7 Continuous Uniform  Coefficient of Variation Parameter Estimates1.8 Exponential 1.9 Erlang   Parameter Estimates1.10 Gamma   Parameter Estimates1.11 Beta   Standard Beta   Mean and Variance  Parameter Estimates1.12    Weibull   Weibull Plot  Parameter Estimates1.13 Normal Standard Normal Distribution  Coefficient of Variation Parameter Estimates1.14 Lognormal     < Parameter Estimates1.15 Summary1.16   Reference2   Discrete Distributions2.1   Introduction2.2   Discrete Random Variables Lexis Ratio2.3   Discrete Uniform Parameter Estimates 2.4   Binomial Lexis Ratio Parameter Estimates Normal Approximation   Poisson Approximation  2.5 Geometric Number of Trials Number of Failures Lexis Ratio Parameter Estimate2.6   Pascal Number of Trials Lexis Ratio  Parameter Estimate Number of Failures Lexis Ratio Parameter Estimate2.7   Poisson Lexis Ratio Relation to the Exponential Distribution Parameter Estimate2.8   Hyper Geometric Parameter Estimate2.9 Summary2.10   Reference3 Standard Normal3.1 Introduction3.2 Gaussian Distribution 3.3 Some Relations on the Standard Normal Distribution4.3 Normal Distribution3.5 Standard Normal3.6     Hastings Approximations Approximation of F(z) from z Approximation of z from F(z) 3.7 Table Values of the Standard Normal 3.8 Discrete Normal Distribution3.9 Summary3.10   References4 Partial Expectation4.1 Introduction4.2 Partial Expectation4.3 Left Location Parameter Table Entries4.4 Inventory Management4.5 Right Location Parameter4.6 Advance Demand4.7   Summary4.8   References5 Left Truncated Normal5.1   Introduction5.2   Left-Location Parameter5.3   Mathematical Equations5.4   Table Entries5.5   More Tables5.6   Left Truncated Distribution5.7 Application to Sample Data5.8   LTN for Inventory Control Automotive Service Parts Distribution Center Retail Products5.9   Summary5.10   References6   Right Truncated Normal6.1   Introduction6.2   Right Truncated Distribution6.3   Mathematical Equations6.4   Variable t Range6.5 Table Entries6.6 Application to Sample Data6.7   More Tables6.8   Summary6.9   Reference7 Truncated Normal Spread Ratio7.1   Introduction7.2   The Spread Ratio7.3   LTN Distribution Measures7.4   LTN Table Entries7.5   RTN Distribution Measures7.6   RTN Table Entries7.7   Estimating the Distribution Type7.8   Selecting the Distribution Type7.9 Estimating the Low and High Limits When LTN Estimate  When LTN When RTN Estimate When RTN When Normal Compute the Adjusted Coefficient of Variation7.10   Find xwhere P(x ≤ x) = 7.11   Find  where P(x ≤ x`) = 7.12   Summary    8   Bivariate Normal 8.1   Introduction 8.2   Bivariate Normal Distribution Marginal Distributions Conditional Distributions 8.3   Bivariate Standard Normal Distribution Conditional Distribution of z2 Conditional Distribution of z1 Cumulative Joint Probability Approximation of F(k1,k2) Table Values of F(k1,k2) 8.4   Some Basic Probabilities for (z1,z2) ~ BVN(0,0,1,1,)8.5   Probabilities for (x1,x2) ~ BVN8.6   Summary8.7   References9     Lognormal9.1 Introduction9.2   Lognormal Distribution9.3   Notation9.4   Lognormal Lognormal Mode  Lognormal Median9.5   Raw Lognormal Variable9.6   Shifted Lognormal Variable9.7   Normal Variable9.8 Zero-Mean Normal Variable9.9 Standard LN Variable9.10 Lognormal Table Entries9.11 Lognormal Distribution Table9.12   Summary9.13   Reference10 Bivariate Lognormal 10.1   Introduction10.2   Bivariate Lognormal       Notation Some Properties Between x and y Mode of x and x`10.3   Lognormal and Normal Notation Related Parameters10.4   Bivariate Lognormal Distribution Bivariate Lognormal Correlation Bivariate Lognormal Designation10.5   Bivariate Normal Distribution10.6   Bivariate (Zero-Mean) Normal Distribution10.7   Bivariate (Standard) Normal Distribution10.8   Summary10.9   References
Höhe
235 mm
Breite
15.5 cm

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