# dependence in probability and statistics 187 lecture notes in statistics

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## Dependence In Probability And Statistics

**Author :**Paul Doukhan

**ISBN :**3642141048

**Genre :**Mathematics

**File Size :**44. 56 MB

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This account of recent works on weakly dependent, long memory and multifractal processes introduces new dependence measures for studying complex stochastic systems and includes other topics such as the dependence structure of max-stable processes.

## Limit Theorems For Associated Random Fields And Related Systems

**Author :**Aleksandr Vadimovich Bulinski?

**ISBN :**9789812709400

**Genre :**Mathematics

**File Size :**22. 62 MB

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This volume is devoted to the study of asymptotic properties of wide classes of stochastic systems arising in mathematical statistics, percolation theory, statistical physics and reliability theory. Attention is paid not only to positive and negative associations introduced in the pioneering papers by Harris, Lehmann, Esary, Proschan, Walkup, Fortuin, Kasteleyn and Ginibre, but also to new and more general dependence conditions. Naturally, this scope comprises families of independent real-valued random variables. A variety of important results and examples of Markov processes, random measures, stable distributions, Ising ferromagnets, interacting particle systems, stochastic differential equations, random graphs and other models are provided. For such random systems, it is worthwhile to establish principal limit theorems of the modern probability theory (central limit theorem for random fields, weak and strong invariance principles, functional law of the iterated logarithm etc.) and discuss their applications.There are 434 items in the bibliography.The book is self-contained, provides detailed proofs, for reader's convenience some auxiliary results are included in the Appendix (e.g. the classical Hoeffding lemma, basic electric current theory etc.).

## Weak Dependence With Examples And Applications

**Author :**Jrme Dedecker

**ISBN :**9780387699516

**Genre :**Mathematics

**File Size :**37. 28 MB

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Time series and random ?elds are main topics in modern statistical techniques. They are essential for applications where randomness plays an important role. Indeed, physical constraints mean that serious modelling cannot be done - ing only independent sequences. This is a real problem because asymptotic properties are not always known in this case. Thepresentworkisdevotedtoprovidingaframeworkforthecommonlyused time series. In order to validate the main statistics, one needs rigorous limit theorems. In the ?eld of probability theory, asymptotic behavior of sums may or may not be analogous to those of independent sequences. We are involved with this ?rst case in this book. Very sharp results have been proved for mixing processes, a notion int- duced by Murray Rosenblatt [166]. Extensive discussions of this topic may be found in his Dependence in Probability and Statistics (a monograph published by Birkhau ̀ˆser in 1986) and in Doukhan (1994) [61], and the sharpest results may be found in Rio (2000)[161]. However, a counterexample of a really simple non-mixing process was exhibited by Andrews (1984) [2]. The notion of weak dependence discussed here takes real account of the available models, which are discussed extensively. Our idea is that robustness of the limit theorems with respect to the model should be taken into account. In real applications, nobody may assert, for example, the existence of a density for the inputs in a certain model, while such assumptions are always needed when dealing with mixing concepts.

## Mathematical Methods Of Statistics

**Author :**

**ISBN :**UOM:39015068685133

**Genre :**Mathematical statistics

**File Size :**44. 18 MB

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## Lietuvos Matematikos Rinkinys

**Author :**

**ISBN :**UOM:39015072627311

**Genre :**Mathematics

**File Size :**39. 36 MB

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## New Perspectives In Econometric Theory

**Author :**Halbert White

**ISBN :**IND:30000094705195

**Genre :**Business & Economics

**File Size :**54. 81 MB

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New Perspectives in Econometric Theory comprises specially selected papers by Halbert White which reflect his research in a variety of related areas in econometrics: heteroskedasticity of unknown form; nonlinear and nonparametric regression; instrumental variables and generalized method of moments estimation; and measurability and limit theory. In many instances, results from one paper provide the foundation for, or suggest new directions for, research taken up by others in the collection. The intent of collecting these papers together in the present volume, with new commentaries by the author, is to provide access both to a modern unified perspective for econometric theory and to a set of concepts and tools that will be useful to practitioners in the field.As a companion to the first volume entitled Advances in Econometric Theory, this latest selection of Halbert White's work will appeal to academics and researchers in econometrics and economic theory.

## Mathematical Reviews

**Author :**

**ISBN :**UOM:39015082440879

**Genre :**Mathematics

**File Size :**34. 40 MB

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## Probability And Mathematical Statistics

**Author :**

**ISBN :**UVA:X002407545

**Genre :**Mathematical statistics

**File Size :**74. 86 MB

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## Dependence In Probability And Statistics

**Author :**Ernst Eberlein

**ISBN :**UOM:39015017931968

**Genre :**Mathematics

**File Size :**31. 75 MB

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## Journal Of The American Statistical Association

**Author :**

**ISBN :**UOM:39015060966952

**Genre :**Statistics

**File Size :**76. 33 MB

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