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[null,"1.","Record Nr.",null,"UNINA9910458777703321"]
[null,null,"Autore",null,"Karian Zaven A."]
[null,null,"Titolo",null,"Handbook of fitting statistical distributions with R / / Zaven A. Karian, Edward J. Dudewicz"]
[null,null,"Pubbl/distr/stampa",null,"Boca Raton : , : CRC Press, , 2011"]
[null,null,"ISBN",null,"0-429-14078-9"]
[{"$nulls":4},"1-58488-712-5"]
[null,null,"Descrizione fisica",null,"1 online resource (1722 p.)"]
[null,null,"Disciplina",null,"519.2/4"]
[null,null,"Soggetti",null,"Distribution (Probability theory)"]
[{"$nulls":4},"R (Computer program language)"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Preface; About the Authors; Dedication; Comments from GLD Pioneers; CONTENTS; PART I: Overview; 1 Fitting Statistical Distributions: An Overview; PART II: The Generalized Lambda Distribution; 2 The Generalized Lambda Family of Distributions; 3 Fitting Distributions and Data with the GLDvia the Method of Moments; 4 The Extended GLD System, the EGLD:Fitting by the Method of Moments; 5 A Percentile-Based Approach to Fitting Distributionsand Data with the GLD; 6 Fitting Distributions and Data with the GLDthrough L-Moments"]
[{"$nulls":4},"7 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)"]
[{"$nulls":4},"14 Fitting GLDs and Mixture of GLDs to Data UsingQuantile Matching Method15 Fitting GLD to Data Using GLDEX 1.0.4 in R; PART IV: Other Families of Distributions; 16 Fitting Distributions and Data with the Johnson Systemvia the Method of Moments; 17 Fitting Distributions and Data with the Kappa Distributionthrough L-Moments and Percentiles; 18 Weighted Distributional Lα Estimates; 19 A Multivariate Gamma "]
[{"$nulls":4},"Distribution for Linearly Related Proportional Outcomes; PART V: The Generalized Bootstrap and Monte Carlo Methods; 20 The Generalized Bootstrap (GB) and Monte Carlo (MC) Methods"]
[{"$nulls":4},"21 The Generalized Bootstrap: A New Fitting Strategy and Simulation Study Showing Advantage over Bootstrap Percentile Methods22 Generalized Bootstrap Confidence Intervals for High Quantiles; PART VI: Assessment of the Quality of Fits; 23 Goodness-of-Fit Criteria Based on Observations Quantized by Hypothetical and Empirical Percentiles; 24 Evidential Support Continuum (ESC): A New Approach to Goodness-of-Fit Assessment, which Addresses Conceptual and Practical Challenges; 25 Estimation of Sampling Distributions of the Overlapping Coefficient and Other Similarity Measures"]
[{"$nulls":4},"PART 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 Modeling"]
[{"$nulls":4},"31 A Rainfall-Based Model for Predicting the Regional Incidence of Wheat Seed Infection by Stagonospora nodorum in New York"]
[null,null,null,"Sommario/riassunto","Strengthened 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 int"]