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|a 519.5/4
|2 23
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|a Peng, Liang.
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| 245 |
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|a Inference for Heavy-Tailed Data :
|b Applications in Insurance and Finance.
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| 264 |
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|a [Place of publication not identified] :
|b Elsevier Science,
|c 2017.
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| 300 |
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|a 1 online resource (182 pages)
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Print version record.
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|a Front Cover; Inference for Heavy-Tailed Data; Copyright; Contents; About the Authors; Preface; 1 Introduction; 1.1 Basic Probability Theory; 1.2 Basic Extreme Value Theory; 2 Heavy Tailed Independent Data; 2.1 Heavy Tail; 2.2 Tail Index Estimation; 2.2.1 Hill Estimator; 2.2.1.1 Asymptotic Properties; 2.2.1.2 Optimal Choice of k; 2.2.1.3 Data Driven Methods for Choosing k; 2.2.1.4 Bias Corrected Estimation; 2.2.1.5 Sample Fraction Choice Motivated by Bias Corrected Estimation; 2.2.2 Other Tail Index Estimators; 2.3 High Quantile Estimation; 2.4 Extreme Tail Probability Estimation.
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|a 2.5 Interval Estimation2.5.1 Con dence Intervals for Tail Index; 2.5.1.1 Normal Approximation Method; 2.5.1.2 Bootstrap Method; 2.5.1.3 Empirical Likelihood Method; 2.5.2 Con dence Intervals for High Quantile; 2.6 Goodness-of-Fit Tests; 2.7 Estimation of Mean; 2.8 Expected Shortfall; 2.9 Haezendonck-Goovaerts (H-G) Risk Measure; 3 Heavy Tailed Dependent Data; 3.1 Tail Empirical Process and Tail Quantile Process; 3.2 Heavy Tailed Dependent Sequence; 3.3 ARMA Model; 3.4 Stochastic Difference Equations; 3.5 Heavy Tailed GARCH Sequences; 3.6 Double AR(1) Model; 3.7 Conditional Value-at-Risk.
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|a 3.8 Heavy Tailed AR-GARCH Sequences3.9 Self-Weighted Estimation for ARMA-GARCH Models; 3.10 Unit Root Tests With In nite Variance Errors; 4 Multivariate Regular Variation; 4.1 Multivariate Regular Variation; 4.2 Hidden Multivariate Regular Variation; 4.3 Tail Dependence and Extreme Risks Under Multivariate Regular Variation; 4.4 Loss Given Default Under Multivariate Regular Variation; 4.5 Estimating an Extreme Set Under Multivariate Regular Variation; 4.6 Extreme Geometric Quantiles Under Multivariate Regular Variation; 5 Applications; 5.1 Some Visualization Tools for Preliminary Analysis.
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| 505 |
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|a 5.1.1 Hill Plot5.1.2 Alternative Hill Plot; 5.1.3 Log-Quantile Plot; 5.2 Heuristic Approach for Training Data; 5.3 Applications to Independent Data; 5.3.1 Automobile Bodily Injury Claims; 5.3.2 Automobile Insurance Claims; 5.3.3 Hospital Costs; 5.3.4 Danish Fire Losses Data; 5.4 Applications to Dependent Data; 5.4.1 Daily Foreign Exchange Rates; 5.4.2 Quarterly S & P 500 Indices; 5.4.3 S & P 500 Weighted Daily Returns; 5.5 Some Comments; A Tables; B List of Notations and Abbreviations; Bibliography; Index; Back Cover.
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| 504 |
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|a Includes bibliographical references and index.
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| 650 |
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|a Mathematical statistics.
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| 650 |
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|a Probabilities.
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| 650 |
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2 |
|a Probability
|0 (DNLM)D011336
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|a Probabilit�es.
|0 (CaQQLa)201-0011592
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|a probability.
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|a MATHEMATICS
|x Applied.
|2 bisacsh
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| 650 |
|
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|a MATHEMATICS
|x Probability & Statistics
|x General.
|2 bisacsh
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| 650 |
|
7 |
|a Mathematical statistics
|2 fast
|0 (OCoLC)fst01012127
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| 650 |
|
7 |
|a Probabilities
|2 fast
|0 (OCoLC)fst01077737
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| 776 |
0 |
8 |
|i Print version:
|z 9780128046760
|z 0128046767
|w (OCoLC)974699115
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| 856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780128046760
|z Texto completo
|
