Coverart for item
The Resource Perspectives on big data analysis : methodologies and applications : International Workshop on Perspectives on High-Dimension Data Anlaysis II, May 30-June 1, 2012, Centre de Recherches Mathématiques, Université de Montréal, Montréal, S. Ejaz Ahmed, editor

Perspectives on big data analysis : methodologies and applications : International Workshop on Perspectives on High-Dimension Data Anlaysis II, May 30-June 1, 2012, Centre de Recherches Mathématiques, Université de Montréal, Montréal, S. Ejaz Ahmed, editor

Label
Perspectives on big data analysis : methodologies and applications : International Workshop on Perspectives on High-Dimension Data Anlaysis II, May 30-June 1, 2012, Centre de Recherches Mathématiques, Université de Montréal, Montréal
Title
Perspectives on big data analysis
Title remainder
methodologies and applications : International Workshop on Perspectives on High-Dimension Data Anlaysis II, May 30-June 1, 2012, Centre de Recherches Mathématiques, Université de Montréal, Montréal
Statement of responsibility
S. Ejaz Ahmed, editor
Title variation
Big data analysis
Creator
Contributor
Editor
Subject
Genre
Language
eng
Summary
This volume contains the proceedings of the International Workshop on Perspectives on High-dimensional Data Analysis II, held May 30-June 1, 2012, at the Centre de Recherches Mathematiques, Universite de Montreal, Montreal, Quebec, Canada. This book collates applications and methodological developments in high-dimensional statistics dealing with interesting and challenging problems concerning the analysis of complex, high-dimensional data with a focus on model selection and data reduction. The chapters contained in this book deal with submodel selection and parameter estimation for an array of interesting models. The book also presents some surprising results on high-dimensional data analysis, especially when signals cannot be effectively separated from the noise, it provides a critical assessment of penalty estimation when the model may not be sparse, and it suggests alternative estimation strategies. Readers can apply the suggested methodologies to a host of applications and also can extend these methodologies in a variety of directions. This volume conveys some of the surprises, puzzles and success stories in big data analysis and related fields. This book is co-published with the Centre de Recherches Mathematiques. --Provided by publisher
Member of
Cataloging source
DLC
Dewey number
519.5/35
Illustrations
illustrations
Index
no index present
LC call number
QA278
LC item number
.I585 2012
Literary form
non fiction
http://bibfra.me/vocab/lite/meetingDate
2012
http://bibfra.me/vocab/lite/meetingName
International Workshop on Perspectives on High-Dimensional Data Analysis
Nature of contents
bibliography
http://library.link/vocab/relatedWorkOrContributorDate
1957-
http://library.link/vocab/relatedWorkOrContributorName
Ahmed, S. E.
Series statement
  • Centre de Recherches Mathématiques proceedings
  • Contemporary mathematics,
Series volume
622
http://library.link/vocab/subjectName
  • Multivariate analysis
  • Artificial intelligence
  • Big data
  • Computer science -- Artificial intelligence -- None of the above, but in this section
  • Statistics -- Multivariate analysis -- Factor analysis and principal components; correspondence analysis
  • Statistics -- Linear inference, regression -- Ridge regression; shrinkage estimators
  • Statistics -- Parametric inference -- Asymptotic properties of tests
  • Statistics -- Nonparametric inference -- Estimation
  • Statistics -- Inference from stochastic processes -- Markov processes: estimation
  • Statistics -- Nonparametric inference -- Nonparametric regression
  • Probability theory and stochastic processes
  • Statistics -- Nonparametric inference -- None of the above, but in this section
  • Statistics -- Multivariate analysis -- Hypothesis testing
  • Artificial intelligence
  • Big data
  • Multivariate analysis
Label
Perspectives on big data analysis : methodologies and applications : International Workshop on Perspectives on High-Dimension Data Anlaysis II, May 30-June 1, 2012, Centre de Recherches Mathématiques, Université de Montréal, Montréal, S. Ejaz Ahmed, editor
Instantiates
Publication
Copyright
Bibliography note
Includes bibliographical references
Carrier category
volume
Carrier MARC source
rdacarrier.
Content category
text
Content type MARC source
rdacontent.
Contents
Principal component analysis (PCA) for high-dimensional data. PCA is dead. Long live PCA / Fan Yang, Kjell Doksum, and Kam-Wah Tsui -- Solving a system of high-dimensional equations by MCMC / Nozer D. Singpurwalla and Joshua Landon -- A slice sampler for the hierarchical poisson/gamma random field model / Jian Kang and Timothy D. Johnson -- A new penalized quasi-likelihood for estimating the number of states in a hidden Markov model / Annaliza McGillivray and Abbas Khalili -- Efficient adaptive estimation strategies in high-dimensional partially linear regression models / Xiaoli Gao and S. Ejaz Ahmed -- Geometry and properties of generalized ridge regression in high dimensions / Hemant Ishwaran and J. Sunil Rao -- Multiple testing for high-dimensional data / Guoqing Diao, Bret Hanlon, and Anand N. Vidyashankar -- On multiple contrast tests and simultaneous confidence intervals in high-dimensional repeated measures designs / Frank Konietschke, Yulia R. Gel, and Edgar Brunner -- Data-driven smoothing can preserve good asymptotic properties / Zhouwang Yang, Huizhi Xie, and Xiaoming Huo -- Variable selection for ultra-high-dimensional logistic models / Pang Du, Pan Wu, and Hua Liang -- Shrinkage estimation and selection for a logistic regression model / Shakhawat Hossain and S. Ejaz Ahmed -- Manifold unfolding by isometric patch alignment with an application in protein structure determination / Pooyan Khajehpour Tadavani, Babak Alipanahi, and Ali Ghodsi
Control code
867916794
Dimensions
26 cm
Extent
xi, 191 pages
Isbn
9781470410421
Isbn Type
(alk. paper)
Lccn
2014000814
Media category
unmediated
Media MARC source
rdamedia.
Other physical details
illustrations
System control number
(OCoLC)867916794
Label
Perspectives on big data analysis : methodologies and applications : International Workshop on Perspectives on High-Dimension Data Anlaysis II, May 30-June 1, 2012, Centre de Recherches Mathématiques, Université de Montréal, Montréal, S. Ejaz Ahmed, editor
Publication
Copyright
Bibliography note
Includes bibliographical references
Carrier category
volume
Carrier MARC source
rdacarrier.
Content category
text
Content type MARC source
rdacontent.
Contents
Principal component analysis (PCA) for high-dimensional data. PCA is dead. Long live PCA / Fan Yang, Kjell Doksum, and Kam-Wah Tsui -- Solving a system of high-dimensional equations by MCMC / Nozer D. Singpurwalla and Joshua Landon -- A slice sampler for the hierarchical poisson/gamma random field model / Jian Kang and Timothy D. Johnson -- A new penalized quasi-likelihood for estimating the number of states in a hidden Markov model / Annaliza McGillivray and Abbas Khalili -- Efficient adaptive estimation strategies in high-dimensional partially linear regression models / Xiaoli Gao and S. Ejaz Ahmed -- Geometry and properties of generalized ridge regression in high dimensions / Hemant Ishwaran and J. Sunil Rao -- Multiple testing for high-dimensional data / Guoqing Diao, Bret Hanlon, and Anand N. Vidyashankar -- On multiple contrast tests and simultaneous confidence intervals in high-dimensional repeated measures designs / Frank Konietschke, Yulia R. Gel, and Edgar Brunner -- Data-driven smoothing can preserve good asymptotic properties / Zhouwang Yang, Huizhi Xie, and Xiaoming Huo -- Variable selection for ultra-high-dimensional logistic models / Pang Du, Pan Wu, and Hua Liang -- Shrinkage estimation and selection for a logistic regression model / Shakhawat Hossain and S. Ejaz Ahmed -- Manifold unfolding by isometric patch alignment with an application in protein structure determination / Pooyan Khajehpour Tadavani, Babak Alipanahi, and Ali Ghodsi
Control code
867916794
Dimensions
26 cm
Extent
xi, 191 pages
Isbn
9781470410421
Isbn Type
(alk. paper)
Lccn
2014000814
Media category
unmediated
Media MARC source
rdamedia.
Other physical details
illustrations
System control number
(OCoLC)867916794

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