Specifying Statistical Models - Lecture Notes in Statistics
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Published By Springer New York

9780387908090, 9781461255031

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Non Parametric Prediction in Stationary Processes

Specifying Statistical Models - Lecture Notes in Statistics ◽

10.1007/978-1-4612-5503-1_5 ◽

1983 ◽

pp. 69-84 ◽

Cited By ~ 9

Author(s):

Denis Bosq

Keyword(s):

Stationary Processes ◽

Non Parametric

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Simulation in the General First Order Autoregressive Process (Unidimensional Normal Case)

Specifying Statistical Models - Lecture Notes in Statistics ◽

10.1007/978-1-4612-5503-1_4 ◽

1983 ◽

pp. 50-68 ◽

Cited By ~ 2

Author(s):

Paul Doukhan

Keyword(s):

Autoregressive Process ◽

Normal Case ◽

First Order

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The Probability Integral Transformation for Non Necessarily Absolutely Continuous Distribution Functions, and its Application to Goodness-of-Fit Tests

Specifying Statistical Models - Lecture Notes in Statistics ◽

10.1007/978-1-4612-5503-1_3 ◽

1983 ◽

pp. 36-49

Author(s):

J. P. Raoult ◽

D. Criticou ◽

D. Terzakis

Keyword(s):

Goodness Of Fit ◽

Integral Transformation ◽

Continuous Distribution ◽

Distribution Functions ◽

Absolutely Continuous ◽

Goodness Of Fit Tests ◽

Probability Integral Transformation ◽

Probability Integral

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Bayesian Approaches to Outliers and Robustness

Specifying Statistical Models - Lecture Notes in Statistics ◽

10.1007/978-1-4612-5503-1_2 ◽

1983 ◽

pp. 13-35 ◽

Cited By ~ 10

Author(s):

A. F. M. Smith

Keyword(s):

Bayesian Approaches

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A Contribution to Robust Principal Component Analysis

Specifying Statistical Models - Lecture Notes in Statistics ◽

10.1007/978-1-4612-5503-1_11 ◽

1983 ◽

pp. 176-181

Author(s):

Jacques Benasseni

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Component Analysis ◽

Robust Principal Component Analysis

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Theory and Applications of Least Squares Approximation in Bayesian Analysis

Specifying Statistical Models - Lecture Notes in Statistics ◽

10.1007/978-1-4612-5503-1_7 ◽

1983 ◽

pp. 93-107 ◽

Cited By ~ 1

Author(s):

M. Mouchart ◽

L. Simar

Keyword(s):

Bayesian Analysis ◽

Least Squares ◽

Least Squares Approximation

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Protecting Against Gross Errors: The Aid of Bayesian Methods

Specifying Statistical Models - Lecture Notes in Statistics ◽

10.1007/978-1-4612-5503-1_1 ◽

1983 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Léopold Simar

Keyword(s):

Bayesian Methods

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Non Parametric Bayesian Statistics: A Stochastic Process Approach

Specifying Statistical Models - Lecture Notes in Statistics ◽

10.1007/978-1-4612-5503-1_8 ◽

1983 ◽

pp. 108-133

Author(s):

J. M. Rolin

Keyword(s):

Stochastic Process ◽

Bayesian Statistics ◽

Process Approach ◽

Non Parametric

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“On the Use of Some Variation Distance Inequalities to Estimate the Difference between Sample and Perturbed Sample”

Specifying Statistical Models - Lecture Notes in Statistics ◽

10.1007/978-1-4612-5503-1_10 ◽

1983 ◽

pp. 163-175

Author(s):

A. Hillion

Keyword(s):

Variation Distance ◽

The Difference

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Approximate Reductions of Bayesian Experiments

Specifying Statistical Models - Lecture Notes in Statistics ◽

10.1007/978-1-4612-5503-1_6 ◽

1983 ◽

pp. 85-92

Author(s):

J. P. Florens

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Specifying Statistical Models - Lecture Notes in StatisticsLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer New York

Non Parametric Prediction in Stationary Processes

Simulation in the General First Order Autoregressive Process (Unidimensional Normal Case)

The Probability Integral Transformation for Non Necessarily Absolutely Continuous Distribution Functions, and its Application to Goodness-of-Fit Tests

Bayesian Approaches to Outliers and Robustness

A Contribution to Robust Principal Component Analysis

Theory and Applications of Least Squares Approximation in Bayesian Analysis

Protecting Against Gross Errors: The Aid of Bayesian Methods

Non Parametric Bayesian Statistics: A Stochastic Process Approach

“On the Use of Some Variation Distance Inequalities to Estimate the Difference between Sample and Perturbed Sample”

Approximate Reductions of Bayesian Experiments

Specifying Statistical Models - Lecture Notes in Statistics
Latest Publications