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005 20181204134420.0
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020 _a9783319415734
_9978-3-319-41573-4
024 7 _a10.1007/978-3-319-41573-4
_2doi
040 _aISI Library, Kolkata
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aMAT029000
_2bisacsh
072 7 _aPBT
_2thema
082 0 4 _a519.5
_223
245 1 0 _aBig and Complex Data Analysis
_h[electronic resource] :
_bMethodologies and Applications /
_cedited by S. Ejaz Ahmed.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2017.
300 _aXIV, 386 p. 85 illus., 55 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aContributions to Statistics,
_x1431-1968
505 0 _aPreface -- Introduction -- Unsupervised Bump Hunting Using Principal Components -- Statistical Process Control Charts as a Tool for Analyzing Big Data -- Empirical Likelihood Test for High Dimensional Generalized Linear Models -- Identifying gene-environment interactions associated with prognosis using penalized quantile regression -- A Computationally Efficient Approach for Modeling Complex and Big Survival Data -- Regularization after marginal learning for ultra-high dimensional regression models -- Tests of concentration for low-dimensional and high-dimensional directional data -- Random Projections For Large-Scale Regression -- How Different are Estimated Genetic Networks of Cancer Subtypes? -- Analysis of correlated data with error-prone response under generalized linear mixed models -- High-Dimensional Classification for Brain Decoding -- Optimal shrinkage estimation in heteroscedastic hierarchical linear models -- Bias-reduced moment estimators of Population Spectral Distribution and their applications -- Testing in the Presence of Nuisance Parameters: Some Comments on Tests Post-Model-Selection and Random Critical Values -- A Mixture of Variance-Gamma Factor Analyzers -- Fast Community Detection in Complex Networks with a K-Depths Classifier.
520 _aThis volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Its peer-reviewed contributions showcase recent advances in variable selection, estimation and prediction strategies for a host of useful models, as well as essential new developments in the field. The continued and rapid advancement of modern technology now allows scientists to collect data of increasingly unprecedented size and complexity. Examples include epigenomic data, genomic data, proteomic data, high-resolution image data, high-frequency financial data, functional and longitudinal data, and network data. Simultaneous variable selection and estimation is one of the key statistical problems involved in analyzing such big and complex data. The purpose of this book is to stimulate research and foster interaction between researchers in the area of high-dimensional data analysis. More concretely, its goals are to: 1) highlight and expand the breadth of existing methods in big data and high-dimensional data analysis and their potential for the advancement of both the mathematical and statistical sciences; 2) identify important directions for future research in the theory of regularization methods, in algorithmic development, and in methodologies for different application areas; and 3) facilitate collaboration between theoretical and subject-specific researchers.
650 0 _aMathematical statistics.
650 0 _aBig data.
650 0 _aStatistical methods.
650 0 _aData mining.
650 1 4 _aStatistical Theory and Methods.
_0http://scigraph.springernature.com/things/product-market-codes/S11001
650 2 4 _aStatistics and Computing/Statistics Programs.
_0http://scigraph.springernature.com/things/product-market-codes/S12008
650 2 4 _aBig Data/Analytics.
_0http://scigraph.springernature.com/things/product-market-codes/522070
650 2 4 _aBiostatistics.
_0http://scigraph.springernature.com/things/product-market-codes/L15020
650 2 4 _aData Mining and Knowledge Discovery.
_0http://scigraph.springernature.com/things/product-market-codes/I18030
700 1 _aAhmed, S. Ejaz.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319415727
776 0 8 _iPrinted edition:
_z9783319415741
776 0 8 _iPrinted edition:
_z9783319823874
830 0 _aContributions to Statistics,
_x1431-1968
856 4 0 _uhttps://doi.org/10.1007/978-3-319-41573-4
912 _aZDB-2-SMA
942 _cEB
950 _aMathematics and Statistics (Springer-11649)
999 _c427192
_d427192