Articoli correlati a Big and Complex Data Analysis: Methodologies and Application...

Big and Complex Data Analysis: Methodologies and Applications - Brossura

 
9783319415741: Big and Complex Data Analysis: Methodologies and Applications

Al momento non sono disponibili copie per questo codice ISBN.

Sinossi

Preface.- 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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

(nessuna copia disponibile)

Cerca:



Inserisci un desiderata

Non riesci a trovare il libro che stai cercando? Continueremo a cercarlo per te. Se uno dei nostri librai lo aggiunge ad AbeBooks, ti invieremo una notifica!

Inserisci un desiderata

Altre edizioni note dello stesso titolo

9783319415727: Big and Complex Data Analysis: Methodologies and Applications

Edizione in evidenza

ISBN 10:  3319415727 ISBN 13:  9783319415727
Casa editrice: Springer Nature, 2017
Rilegato