• Anglický jazyk

Model-Based Recursive Partitioning with Adjustment for Measurement Error

Autor: Hanna Birke

¿Model-based recursive partitioning (MOB) provides a powerful synthesis between machine-learning inspired recursive partitioning methods and regression models. Hanna Birke extends this approach by allowing in addition for measurement error in covariates,... Viac o knihe

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49.49 €

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O knihe

¿Model-based recursive partitioning (MOB) provides a powerful synthesis between machine-learning inspired recursive partitioning methods and regression models. Hanna Birke extends this approach by allowing in addition for measurement error in covariates, as frequently occurring in biometric (or econometric) studies, for instance, when measuring blood pressure or caloric intake per day. After an introduction into the background, the extended methodology is developed in detail for the Cox model and the Weibull model, carefully implemented in R, and investigated in a comprehensive simulation study.

  • Vydavateľstvo: Springer Fachmedien Wiesbaden
  • Rok vydania: 2015
  • Formát: Paperback
  • Rozmer: 210 x 148 mm
  • Jazyk: Anglický jazyk
  • ISBN: 9783658085049

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