Dependence in Probability and Statistics
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22

(FIVE YEARS 0)

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9

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Published By Birkhäuser Boston

9781461581635, 9781461581628

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Basic Properties of Strong Mixing Conditions

Dependence in Probability and Statistics ◽

10.1007/978-1-4615-8162-8_8 ◽

1986 ◽

pp. 165-192 ◽

Cited By ~ 87

Author(s):

Richard C. Bradley

Keyword(s):

Strong Mixing ◽

Mixing Conditions ◽

Basic Properties

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Infinitely Divisible Distributions; Gibbs States and Correlations

Dependence in Probability and Statistics ◽

10.1007/978-1-4615-8162-8_16 ◽

1986 ◽

pp. 361-381

Author(s):

Ed Waymire

Keyword(s):

Gibbs States ◽

Infinitely Divisible Distributions ◽

Infinitely Divisible

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Limit Laws for Generalizations of Martingales

Dependence in Probability and Statistics ◽

10.1007/978-1-4615-8162-8_14 ◽

1986 ◽

pp. 335-345

Author(s):

Ernst Eberlein

Keyword(s):

Limit Laws

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On Martingale Central Limit Theory

Dependence in Probability and Statistics ◽

10.1007/978-1-4615-8162-8_13 ◽

1986 ◽

pp. 303-334 ◽

Cited By ~ 10

Author(s):

Peter Gaenssler ◽

Erich Haeusler

Keyword(s):

Central Limit ◽

Limit Theory ◽

Central Limit Theory

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Multivariate Appell polynomials and the central limit theorem

Dependence in Probability and Statistics ◽

10.1007/978-1-4615-8162-8_2 ◽

1986 ◽

pp. 21-71 ◽

Cited By ~ 24

Author(s):

L. Giraitis ◽

D. Surgailis

Keyword(s):

Central Limit Theorem ◽

Limit Theorem ◽

Central Limit ◽

Appell Polynomials ◽

The Central Limit Theorem

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Uniform Integrability and the Central Limit Theorem for Strongly Mixing Processes

Dependence in Probability and Statistics ◽

10.1007/978-1-4615-8162-8_11 ◽

1986 ◽

pp. 269-289 ◽

Cited By ~ 9

Author(s):

Manfred Denker ◽

C. M. Goldie ◽

G. J. Morrow

Keyword(s):

Central Limit Theorem ◽

Limit Theorem ◽

Central Limit ◽

Uniform Integrability ◽

Mixing Processes ◽

The Central Limit Theorem ◽

Strongly Mixing ◽

Strongly Mixing Processes

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Invariance Principles for Independent and Weakly Dependent Random Variables

Dependence in Probability and Statistics ◽

10.1007/978-1-4615-8162-8_10 ◽

1986 ◽

pp. 225-268 ◽

Cited By ~ 24

Author(s):

Walter Philipp

Keyword(s):

Random Variables ◽

Dependent Random Variables ◽

Invariance Principles ◽

Weakly Dependent Random Variables ◽

Weakly Dependent

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On Central and Non-Central Limit Theorems for Non-Linear Functions of a Stationary Gaussian Process

Dependence in Probability and Statistics ◽

10.1007/978-1-4615-8162-8_1 ◽

1986 ◽

pp. 3-19 ◽

Cited By ~ 1

Author(s):

Tze-Chien Sun ◽

Hwai-Chung Ho

Keyword(s):

Gaussian Process ◽

Central Limit ◽

Limit Theorems ◽

Central Limit Theorems ◽

Stationary Gaussian Process ◽

Linear Functions ◽

Non Linear

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Hausdorff dimension of sample paths for self-similar processes

Dependence in Probability and Statistics ◽

10.1007/978-1-4615-8162-8_5 ◽

1986 ◽

pp. 109-117 ◽

Cited By ~ 4

Author(s):

Norio Kôno

Keyword(s):

Hausdorff Dimension ◽

Sample Paths ◽

Self Similar

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Using Renewal Processes to Generate Long-Range Dependence and High Variability

Dependence in Probability and Statistics ◽

10.1007/978-1-4615-8162-8_3 ◽

1986 ◽

pp. 73-89 ◽

Cited By ~ 78

Author(s):

Murad S. Taqqu ◽

Joshua B. Levy

Keyword(s):

Long Range ◽

High Variability ◽

Long Range Dependence ◽

Renewal Processes

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