Verlag: Cambridge University Press CUP, 2019
ISBN 10: 110718486X ISBN 13: 9781107184862
Sprache: Englisch
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ISBN 10: 110718486X ISBN 13: 9781107184862
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In den WarenkorbHardcover. Zustand: new. Hardcover. This tutorial reference serves as a coherent overview of various statistical and mathematical approaches used in brain network analysis, where modeling the complex structures and functions of the human brain often poses many unique computational and statistical challenges. This book fills a gap as a textbook for graduate students while simultaneously articulating important and technically challenging topics. Whereas most available books are graph theory-centric, this text introduces techniques arising from graph theory and expands to include other different models in its discussion on network science, regression, and algebraic topology. Links are included to the sample data and codes used in generating the book's results and figures, helping to empower methodological understanding in a manner immediately usable to both researchers and students. This tutorial reference provides a coherent overview of statistical and mathematical approaches used in brain network analysis. It goes beyond graph theory to explore different models in network science, regression, and algebraic topology, empowering methodological understanding in a manner immediately usable to both researchers and students. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Verlag: Cambridge University Press, 2019
ISBN 10: 110718486X ISBN 13: 9781107184862
Sprache: Englisch
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Verlag: Cambridge University Press, 2019
ISBN 10: 110718486X ISBN 13: 9781107184862
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ISBN 10: 110718486X ISBN 13: 9781107184862
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ISBN 10: 110718486X ISBN 13: 9781107184862
Sprache: Englisch
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Verlag: Cambridge University Press, Cambridge, 2019
ISBN 10: 110718486X ISBN 13: 9781107184862
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In den WarenkorbHardcover. Zustand: new. Hardcover. This tutorial reference serves as a coherent overview of various statistical and mathematical approaches used in brain network analysis, where modeling the complex structures and functions of the human brain often poses many unique computational and statistical challenges. This book fills a gap as a textbook for graduate students while simultaneously articulating important and technically challenging topics. Whereas most available books are graph theory-centric, this text introduces techniques arising from graph theory and expands to include other different models in its discussion on network science, regression, and algebraic topology. Links are included to the sample data and codes used in generating the book's results and figures, helping to empower methodological understanding in a manner immediately usable to both researchers and students. This tutorial reference provides a coherent overview of statistical and mathematical approaches used in brain network analysis. It goes beyond graph theory to explore different models in network science, regression, and algebraic topology, empowering methodological understanding in a manner immediately usable to both researchers and students. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Verlag: Cambridge University Press, Cambridge, 2019
ISBN 10: 110718486X ISBN 13: 9781107184862
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. This tutorial reference serves as a coherent overview of various statistical and mathematical approaches used in brain network analysis, where modeling the complex structures and functions of the human brain often poses many unique computational and statistical challenges. This book fills a gap as a textbook for graduate students while simultaneously articulating important and technically challenging topics. Whereas most available books are graph theory-centric, this text introduces techniques arising from graph theory and expands to include other different models in its discussion on network science, regression, and algebraic topology. Links are included to the sample data and codes used in generating the book's results and figures, helping to empower methodological understanding in a manner immediately usable to both researchers and students. This tutorial reference provides a coherent overview of statistical and mathematical approaches used in brain network analysis. It goes beyond graph theory to explore different models in network science, regression, and algebraic topology, empowering methodological understanding in a manner immediately usable to both researchers and students. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.