05527oam 2200709I 450 991045877770332120200520144314.00-429-14078-91-58488-712-510.1201/b10159 (CKB)2670000000060716(EBL)624984(OCoLC)693330331(SSID)ssj0000419201(PQKBManifestationID)11267896(PQKBTitleCode)TC0000419201(PQKBWorkID)10382145(PQKB)11762303(MiAaPQ)EBC624984(MiAaPQ)EBC4009999(PPN)165238194(Au-PeEL)EBL624984(CaPaEBR)ebr10433633(CaONFJC)MIL698053(Au-PeEL)EBL4009999(OCoLC)781319007(EXLCZ)99267000000006071620180331d2011 uy 0engur|n|---|||||txtccrHandbook of fitting statistical distributions with R /Zaven A. Karian, Edward J. DudewiczBoca Raton :CRC Press,2011.1 online resource (1722 p.)Description based upon print version of record.1-322-66771-3 1-58488-711-7 Includes bibliographical references and index.Preface; About the Authors; Dedication; Comments from GLD Pioneers; CONTENTS; PART I: Overview; 1 Fitting Statistical Distributions: An Overview; PART II: The Generalized Lambda Distribution; 2 The Generalized Lambda Family of Distributions; 3 Fitting Distributions and Data with the GLDvia the Method of Moments; 4 The Extended GLD System, the EGLD:Fitting by the Method of Moments; 5 A Percentile-Based Approach to Fitting Distributionsand Data with the GLD; 6 Fitting Distributions and Data with the GLDthrough L-Moments7 Fitting a Generalized Lambda Distribution Using aPercentile-KS (P-KS) Adequacy Criterion8 Fitting Mixture Distributions Using a Mixture of GeneralizedLambda Distributions with Computer Code; 9 GLD-2: The Bivariate GLD Distribution; 10 Fitting the Generalized Lambda Distribution with Locationand Scale-Free Shape Functionals; 11 Statistical Design of Experiments: A Short Review; PART III: Quantile Distribution Methods; 12 Statistical Modeling Based on Quantile DistributionFunctions; 13 Distribution Fitting with the Quantile Function ofResponse Modeling Methodology (RMM)14 Fitting GLDs and Mixture of GLDs to Data UsingQuantile Matching Method15 Fitting GLD to Data Using GLDEX 1.0.4 in R; PART IV: Other Families of Distributions; 16 Fitting Distributions and Data with the Johnson Systemvia the Method of Moments; 17 Fitting Distributions and Data with the Kappa Distributionthrough L-Moments and Percentiles; 18 Weighted Distributional Lα Estimates; 19 A Multivariate Gamma Distribution for Linearly Related Proportional Outcomes; PART V: The Generalized Bootstrap and Monte Carlo Methods; 20 The Generalized Bootstrap (GB) and Monte Carlo (MC) Methods21 The Generalized Bootstrap: A New Fitting Strategy and Simulation Study Showing Advantage over Bootstrap Percentile Methods22 Generalized Bootstrap Confidence Intervals for High Quantiles; PART VI: Assessment of the Quality of Fits; 23 Goodness-of-Fit Criteria Based on Observations Quantized by Hypothetical and Empirical Percentiles; 24 Evidential Support Continuum (ESC): A New Approach to Goodness-of-Fit Assessment, which Addresses Conceptual and Practical Challenges; 25 Estimation of Sampling Distributions of the Overlapping Coefficient and Other Similarity MeasuresPART VII: Applications26 Fitting Statistical Distribution Functions to Small Datasets; 27 Mixed Truncated Random Variable Fitting with the GLD, and Applications in Insurance and Inventory Management; 28 Distributional Modeling of Pipeline Leakage Repair Costs for a Water Utility Company; 29 Use of the Generalized Lambda Distribution in Materials Science, with Examples in Fatigue Lifetime, Fracture Mechanics, Polycrystalline Calculations, and Pitting Corrosion; 30 Fitting Statistical Distributions to Data in Hurricane Modeling31 A Rainfall-Based Model for Predicting the Regional Incidence of Wheat Seed Infection by Stagonospora nodorum in New YorkStrengthened by examples taken from the scientific literature, this handbook provides statisticians and researchers across the physical and social sciences with cutting-edge methods for fitting continuous probability distributions. It presents families with wide-ranging applicability, including Johnson's system, kappa distribution, and generalized lambda distribution. By providing the necessary R programs, the book enables practitioners to implement the techniques using R computer code. To cover distribution method combinations not included in the book's extensive tables, the authors delve intDistribution (Probability theory)R (Computer program language)Electronic books.Distribution (Probability theory)R (Computer program language)519.2/4Karian Zaven A.103489Dudewicz Edward J103490MiAaPQMiAaPQMiAaPQBOOK9910458777703321Handbook of fitting statistical distributions with R759693UNINA