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1. Extreme Value Theory : An Introduction
by Laurens Haan, Ana Ferreira
出版情報: New York, NY : Springer Science+Business Media, LLC, 2006
シリーズ名: Springer Series in Operations Research and Financial Engineering ;
オンライン: http://dx.doi.org/10.1007/0-387-34471-3
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2. Advances in Distribution Theory, Order Statistics, and Inference
edited by N. Balakrishnan, José María Sarabia, Enrique Castillo
出版情報: Boston, MA : Birkhäuser Boston, 2006
シリーズ名: Statistics for Industry and Technology ;
オンライン: http://dx.doi.org/10.1007/0-8176-4487-3
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3. Lagrangian Probability Distributions
by Prem C. Consul, Felix Famoye
出版情報: Boston, MA : Birkhäuser Boston, 2006
オンライン: http://dx.doi.org/10.1007/0-8176-4477-6
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4. Mathematical and Statistical Models and Methods in Reliability : Applications to Medicine, Finance, and Quality Control
edited by V.V. Rykov, N. Balakrishnan, M.S. Nikulin
出版情報: Boston : Springer Science+Business Media, LLC, 2011
シリーズ名: Statistics for Industry and Technology ;
オンライン: http://dx.doi.org/10.1007/978-0-8176-4971-5
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5. Scan Statistics : Methods and Applications
edited by Joseph Glaz, Vladimir Pozdnyakov, Sylvan Wallenstein
出版情報: Boston : Birkhäuser Boston, 2009
シリーズ名: Statistics for Industry and Technology ;
オンライン: http://dx.doi.org/10.1007/978-0-8176-4749-0
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6. Parametric Statistical Change Point Analysis : With Applications to Genetics, Medicine, and Finance. Second Edition
by Jie Chen, Arjun K. Gupta
出版情報: Boston : Birkhäuser Boston, 2012
オンライン: http://dx.doi.org/10.1007/978-0-8176-4801-5
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7. Probability with Statistical Applications
by Rinaldo B. Schinazi
出版情報: Boston : Springer Science+Business Media, LLC, 2012
オンライン: http://dx.doi.org/10.1007/978-0-8176-8250-7
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8. Heavy-Tail Phenomena : Probabilistic and Statistical Modeling
by Sidney I. Resnick
出版情報: New York, NY : Springer Science+Business Media, LLC, 2007
シリーズ名: Springer Series in Operations Research and Financial Engineering ;
オンライン: http://dx.doi.org/10.1007/978-0-387-45024-7
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9. Advances in Statistical Methods for the Health Sciences : Applications to Cancer and AIDS Studies, Genome Sequence Analysis, and Survival Analysis
edited by Jean-Louis Auget, N. Balakrishnan, Mounir Mesbah et al
出版情報: Boston, MA : Birkhäuser Boston, 2007
シリーズ名: Statistics for Industry and Technology ;
オンライン: http://dx.doi.org/10.1007/978-0-8176-4542-7
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10. Statistical Models and Methods for Biomedical and Technical Systems
edited by Filia Vonta, Mikhail Nikulin, Nikolaos Limnios, Catherine Huber-Carol
出版情報: Boston, MA : Birkhäuser Boston, 2008
シリーズ名: Statistics for Industry and Technology ;
オンライン: http://dx.doi.org/10.1007/978-0-8176-4619-6
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11. Advances in Data Analysis : Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks
edited by Christos H. Skiadas
出版情報: Boston : Birkhäuser Boston, 2010
シリーズ名: Statistics for Industry and Technology ;
オンライン: http://dx.doi.org/10.1007/978-0-8176-4799-5
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12. Analytical Methods in Statistics : AMISTAT, Liberec, Czech Republic, September 2019. 1st ed. 2020
edited by Matúš Maciak, Michal Pešta, Martin Schindler
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
シリーズ名: Springer Proceedings in Mathematics & Statistics ; 329
オンライン: https://doi.org/10.1007/978-3-030-48814-7
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目次情報: 続きを見る
Preface
Y. Güney, J. Jurečková and O. Arslan, Averaged Autoregression Quantiles in Autoregressive Model
J. Kalina and P. Vidnerová, Regression Neural Networks with a Highly Robust Loss Function
H. L. Koul and P. Geng, Weighted Empirical Minimum Distance Estimators in Berkson Measurement Error Regression Models
M. Maciak, M. Pešta and S. Vitali, Implied Volatility Surface Estimation via Quantile Regularization
I. Mizera, A remark on the Grenander estimator
U. Radojičić and K. Nordhausen, Non-Gaussian Component Analysis: Testing the Dimension of the Signal Subspace
P. Vidnerová, J. Kalina and Y. Güney, A Comparison of Robust Model Choice Criteria within a Metalearning Study
S. Zwanzig and R. Ahmad, On Parameter Estimation for High Dimensional Errors-in-Variables Models
Preface
Y. Güney, J. Jurečková and O. Arslan, Averaged Autoregression Quantiles in Autoregressive Model
J. Kalina and P. Vidnerová, Regression Neural Networks with a Highly Robust Loss Function
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13. Heavy-Tailed Time Series. 1st ed. 2020
by Rafal Kulik, Philippe Soulier
出版情報: New York, NY : Springer New York : Imprint: Springer, 2020
シリーズ名: Springer Series in Operations Research and Financial Engineering ;
オンライン: https://doi.org/10.1007/978-1-0716-0737-4
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Regular variation
Regularly varying random variables
Regularly varying random vectors
Dealing with extremal independence
Regular variation of series and random sums
Regularly varying time series
Limit theorems
Convergence of clusters-. Point process convergence
Convergence to stable and extremal processes
The tall empirical and quantile processes
Estimation of cluster functionals
Estimation for extremally independent time series
Bootstrap
Time series models
Max-stable processes
Markov chains
Moving averages
Long memory processes
Appendices
Regular variation
Regularly varying random variables
Regularly varying random vectors
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14. Univariate Stable Distributions : Models for Heavy Tailed Data. 1st ed. 2020
by John P. Nolan
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
シリーズ名: Springer Series in Operations Research and Financial Engineering ;
オンライン: https://doi.org/10.1007/978-3-030-52915-4
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Basic Properties of Univariate Stable Distributions
Modeling with Stable Distributions
Technical Results for Univariate Stable Distributions
Univariate Estimation
Stable Regression
Signal Processing with Stable Distributions
Related Distributions
Appendix A: Mathematical Facts
Appendix B: Stable Quantiles
Appendix C: Stable Modes
Appendix D: Asymptotic Standard Deviations of ML Estimators
Basic Properties of Univariate Stable Distributions
Modeling with Stable Distributions
Technical Results for Univariate Stable Distributions
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15. Statistics Based on Dirichlet Processes and Related Topics. 1st ed. 2020
by Hajime Yamato
出版情報: Singapore : Springer Singapore : Imprint: Springer, 2020
シリーズ名: JSS Research Series in Statistics ;
オンライン: https://doi.org/10.1007/978-981-15-6975-3
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Introduction
Dirichlet process and Chinese restaurant process
Nonparametric estimation of estimable parameter
Random partition of positive integer
Introduction
Dirichlet process and Chinese restaurant process
Nonparametric estimation of estimable parameter