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Multivariate Families with Mixture Dependence

represented by the tool of divided di erences, actually known in numerical analysis. The results are illustrated with examples of multivariate Pareto;

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Dependence Modeling with Copulas

Dependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including;

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Dependence Modeling with Copulas

Dependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including;

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Copulas for Risk Management

be modeled and the scale-invariant measures of dependence might be considered. With this problem in popularity has come a rise in the need;

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Multivariate Models and Multivariate Dependence Concepts

This book on multivariate models, statistical inference, and data analysis contains deep coverage of;...

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The Valuation of Multivariate Options

. Thereby, the special features of financial return data are tried to be taken into account. Advancing option valuation theory to options with;

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Optimal Mixture Experiments

of mixture designs in areas like agriculture, pharmaceutics and food and beverages have been presented. Familiarity with the basic concepts of design;

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Cluster Analysis 5th

coverage of the latest developments in the field and a new chapter dealing with finite mixture models for structured data. Real life examples are;

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Multivariate Generalized Linear Mixed Models Using R

information on quadrature, model estimation, and endogenous variables, along with SabreR commands and examples. Improve Your Longitudinal StudyIn;

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Statistical Modeling Using Local Gaussian Approximation

discriminant. Reviews local dependence modeling with applications to time series and finance markets Introduces new techniques;

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Handbook of Mixture Analysis

, networks, and much more. Mixture analysis is a very active research topic in statistics and machine learning, with new developments in methodology;

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Discrete Multivariate Distributions

, hypergeometric, Polya-Eggenberger, Ewens, orders, and some families of distributions. Discrete Multivariate Distributions begins with a general overview;

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Universal Time-Series Forecasting with Mixture Predictors

The author considers the problem of sequential probability forecasting in the most general setting, ;...

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Contributions to Static and Time-Varying Copula-Based Modeling of Multivariate Association

with either a specified or unspecified change point (candidate) are derived. The thesis concludes with a study of characterizations;

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Continuous Multivariate Distributions

Pareto distributions, as well as MV natural exponential families, which have grown immensely since the 1970s. Each distribution is presented;

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Copulas and Its Application in Hydrology and Water Resources

, scientists and engineers working in hydrology and water resources, and will also benefit graduate or doctoral students with a basic grasp of copula;

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Clinical Interventions with Gang Adolescents and Their Families

of gang youth and their families. Providing a well-integrated mixture of theory, clinical axioms, and practical ideas, the book offers invaluable;

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Analysis of Multivariate Social Science Data

Editionenables a basic understanding of how to use key multivariate methods in the social sciences. With updates in every chapter, this edition expands;

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Elements of Copula Modeling with R

distributions using copulas can be carried out in the R statistical environment with the package copula (among others). Copulas are multivariate;

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Copulae and Multivariate Probability Distributions in Finance

many problems in financial econometrics. This book describes the state of the art in tools required to deal with these observed features;

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Models for Dependent Time Series

approaches with spectral methods for identifying causal dependence between time series. Web ResourceA supplementary website provides the data;

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Models for Dependent Time Series

approaches with spectral methods for identifying causal dependence between time series. Web Resource A supplementary website provides the data sets;

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Analysis of Multivariate Social Science Data, Second Edition

Editionenables a basic understanding of how to use key multivariate methods in the social sciences. With updates in every chapter, this edition expands;

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A Multivariate Claim Count Model for Applications in Insurance

, the model balances interesting stylized facts (such as dependence across the components, over-dispersion and the clustering of claims) with a;

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Multivariate Permutation Tests

relations between variables. Provides a clear exposition of the use of multivariate permutation testing, with emphasis on the use of nonparametric;

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Applied Multivariate Statistics With Sas Software, Second Edition + Multivariate Data Reduction And Discrimination With Sas Software Set

This set contains 9780471322993 Applied Multivariate Statistics with SAS? Software, 2nd Edition and 9780471323006 Multivariate Data;

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Extreme Value Modeling and Risk Analysis

along with the most recent methodologies and various applications. The book brings together background material and advanced topics, eliminating;

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