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  2. Matematik
  3. Sandsynlighedsregning og statistik
Sparse Graphical Modeling for High Dimensional Data
- A Paradigm of Conditional Independence Tests
Af: Faming Liang, Bochao Jia
Engelsk Hardback
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Sparse Graphical Modeling for High Dimensional Data
- A Paradigm of Conditional Independence Tests
Af: Faming Liang, Bochao Jia
Engelsk Hardback
Hardback
1.148 kr
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Sikker betaling
6 - 8 hverdage
Om denne bog

This book provides a general framework for learning sparse graphical models with conditional independence tests. It includes complete treatments for Gaussian, Poisson, multinomial, and mixed data; unified treatments for covariate adjustments, data integration, and network comparison; unified treatments for missing data and heterogeneous data; efficient methods for joint estimation of multiple graphical models; effective methods of high-dimensional variable selection; and effective methods of high-dimensional inference. The methods possess an embarrassingly parallel structure in performing conditional independence tests, and the computation can be significantly accelerated by running in parallel on a multi-core computer or a parallel architecture. This book is intended to serve researchers and scientists interested in high-dimensional statistics, and graduate students in broad data science disciplines.

Key Features:

  • A general framework for learning sparse graphical models with conditional independence tests

  • Complete treatments for different types of data, Gaussian, Poisson, multinomial, and mixed data

  • Unified treatments for data integration, network comparison, and covariate adjustment

  • Unified treatments for missing data and heterogeneous data

  • Efficient methods for joint estimation of multiple graphical models

  • Effective methods of high-dimensional variable selection

  • Effective methods of high-dimensional inference
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Product detaljer
Sprog:
Engelsk
Sider:
130
ISBN-13:
9780367183738
Indbinding:
Hardback
Udgave:
ISBN-10:
0367183730
Kategori:
Udg. Dato:
2 aug 2023
Længde:
14mm
Bredde:
242mm
Højde:
162mm
Forlag:
Taylor & Francis Ltd
Oplagsdato:
2 aug 2023
Forfatter(e):
Kategori sammenhænge