Count Time Series, 

Автор: Hamilton, James
Название: Time Series Analysis
ISBN: 0691042896 ISBN-13(EAN): 9780691042893
Издательство: Wiley
Рейтинг:
Цена: 73920.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A graduate-level text which describes the recent dramatic changes that have taken place in the way that researchers analyze economic and financial time series. It explores such important innovations as vector regression, nonlinear time series models and the generalized methods of moments.

Автор: Durbin, James; Koopman, Siem Jan
Название: Time Series Analysis by State Space Methods
ISBN: 019964117X ISBN-13(EAN): 9780199641178
Издательство: Oxford Academ
Рейтинг:
Цена: 126720.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This new edition updates Durbin & Koopman`s important text on the state space approach to time series analysis providing a more comprehensive treatment, including the filtering of nonlinear and non-Gaussian series. The book provides an excellent source for the development of practical courses on time series analysis.

Автор: Beeler Robert A.
Название: How to Count
ISBN: 3319355082 ISBN-13(EAN): 9783319355085
Издательство: Springer
Рейтинг:
Цена: 41920.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Providing a self-contained resource for upper undergraduate courses in combinatorics, this text emphasizes computation, problem solving, and proof technique. When possible, the book introduces concepts using combinatorial methods (as opposed to induction or algebra) to prove identities.

Автор: Friendly, Michael Meyer, David
Название: Discrete data analysis with r
ISBN: 149872583X ISBN-13(EAN): 9781498725835
Издательство: Taylor&Francis
Рейтинг:
Цена: 93910.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.

Автор: Daniela Anna Selch; Matthias Scherer
Название: A Multivariate Claim Count Model for Applications in Insurance
ISBN: 3030065375 ISBN-13(EAN): 9783030065379
Издательство: Springer
Рейтинг:
Цена: 46570.00 T
Наличие на складе: Поставка под заказ.
Описание: This monograph presents a time-dynamic model for multivariate claim counts in actuarial applications.Inspired by real-world claim arrivals, the model balances interesting stylized facts (such as dependence across the components, over-dispersion and the clustering of claims) with a high level of mathematical tractability (including estimation, sampling and convergence results for large portfolios) and can thus be applied in various contexts (such as risk management and pricing of (re-)insurance contracts). The authors provide a detailed analysis of the proposed probabilistic model, discussing its relation to the existing literature, its statistical properties, different estimation strategies as well as possible applications and extensions. Actuaries and researchers working in risk management and premium pricing will find this book particularly interesting. Graduate-level probability theory, stochastic analysis and statistics are required.

Автор: Sun, Jianguo Zhao, Xingqiu
Название: Statistical analysis of panel count data
ISBN: 1461487145 ISBN-13(EAN): 9781461487142
Издательство: Springer
Рейтинг:
Цена: 93160.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Statistical Analysis of Panel Count Data

Автор: Beeler Robert
Название: How to Count
ISBN: 331913843X ISBN-13(EAN): 9783319138435
Издательство: Springer
Рейтинг:
Цена: 41920.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: How to Count

Автор: Hilbe
Название: Modeling Count Data
ISBN: 1107028337 ISBN-13(EAN): 9781107028333
Издательство: Cambridge Academ
Рейтинг:
Цена: 102430.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written for researchers with little or no background in advanced statistics, this book provides guidelines and fully worked examples of how to select, construct, interpret and evaluate the full range of count models. Stata, R, and SAS code enable readers in a variety of disciplines to adapt models for their own purposes.

Автор: Donald B. Percival, Andrew T. Walden
Название: Spectral Analysis for Univariate Time Series
ISBN: 1107028140 ISBN-13(EAN): 9781107028142
Издательство: Cambridge Academ
Рейтинг:
Цена: 97150.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Spectral analysis is an important technique for interpreting time series data. This book uses the R language and real world examples to show data analysts interested in time series in the environmental, engineering and physical sciences how to bridge the gap between the statistical theory behind spectral analysis and its application to actual data.

Автор: Manfred Mudelsee
Название: Climate Time Series Analysis
ISBN: 3319044494 ISBN-13(EAN): 9783319044491
Издательство: Springer
Рейтинг:
Цена: 158380.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written for climatologists and applied statisticians, this book explains the bootstrap algorithms (including novel adaptions) and methods for confidence interval construction. The accuracy of the algorithms is tested by means of Monte Carlo experiments.

Автор: Gebhard Kirchg?ssner; J?rgen Wolters; Uwe Hassler
Название: Introduction to Modern Time Series Analysis
ISBN: 3642440290 ISBN-13(EAN): 9783642440298
Издательство: Springer
Рейтинг:
Цена: 69830.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents modern methods of time series econometrics and their applications to macroeconomics and finance. It includes numerous examples and analyses based on real economic data.

Автор: Levendis John D.
Название: Time Series Econometrics: Learning Through Replication
ISBN: 3319982818 ISBN-13(EAN): 9783319982816
Издательство: Springer
Рейтинг:
Цена: 111790.00 T
Наличие на складе: Невозможна поставка.
Описание: Finally, students estimate multi-equation models such as vector autoregressions and vector error-correction mechanisms, replicating the results in influential papers by Sims and Granger. The book contains many worked-out examples, and many data-driven exercises.