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Statistical Modeling and Analysis for Complex Data Problems (Gerad 25th Anniversary)
 
 
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Statistical Modeling and Analysis for Complex Data Problems (Gerad 25th Anniversary) [Hardcover]

Pierre Duchesne (Editor), Bruno Rémillard (Editor)

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Book Description

0387245545 978-0387245546 April 12, 2005 1

Statistical Modeling and Analysis for Complex Data Problems treats some of today’s more complex problems and it reflects some of the important research directions in the field. Twenty-nine authors – largely from Montreal’s GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes – present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.


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From the Back Cover

STATISTICAL MODELING AND ANALYSIS FOR COMPLEX DATA PROBLEMS treats some of today's more complex problems and it reflects some of the important research directions in the field. Twenty-nine authorsâlargely from Montreal's GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processesâpresent survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains. Some of the areas and topics examined in the volume are: an analysis of complex survey data, the 2000 American presidential election in Florida, data mining, estimation of uncertainty for machine learning algorithms, interacting stochastic processes, dependent data & copulas, Bayesian analysis of hazard rates, re-sampling methods in a periodic replacement problem, statistical testing in genetics and for dependent data, statistical analysis of time series analysis, theoretical and applied stochastic processes, and an efficient non linear filtering algorithm for the position detection of multiple targets. The book examines the methods and problems from a modeling perspective and surveys the state of current research on each topic and provides direction for further research exploration of the area.

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Inside This Book (learn more)
First Sentence:
The study of meta-elliptical multivariate distributions was recently launched by Fang, Fang and Kotz (2002), and their extension of the meta-Gaussian family of distributions due to Krzysztofowicz and Kelly (1996) is sure to find its way gradually into statistical, actuarial, economic and financial applications, where elliptically contoured distributions are already in common use. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
cluster correlated data, bisquare families, echelon representation, one with the highest power, asymptotic covariance structure, good rate function, empirical coverage probabilities, strong white noise, modified histograms, hazard rate estimation, weak white noise, long autoregression, additive outliers, robust test statistics, mallows types, elliptically contoured distribution, portmanteau test, information divergence, large deviations principles, contoured distributions, bootstrap confidence intervals, white noise assumption, significance limits, false discovery rate, elementary transitions
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Del Moral, The Annals of Statistics, Journal of the American Statistical Association, Journal of Time Series Analysis, Journal of Multivariate Analysis, Journal of the Royal Statistical Society, Distribution Sample Bootstrap, Log Scale, Statistical Science, The Canadian Journal of Statistics, Journal of Econometrics, Out of Line The Statistical Evidence, Pat Buchanan, Probability Letters, Replacement Policies, Sanov's Theorem, State of Florida, The Annals of Mathematical Statistics, The Fib, Applied Statistics, Bias Rel, Design Distribution Value Test, Electoral College, Lecture Notes
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