Kniha Model-Based Recursive Partitioning with Adjustment for Measurement Error Hanna Birke

Model-Based Recursive Partitioning with Adjustment for Measurement Error

Applied to the Cox's Proportional Hazards and Weibull Model

Autor: Hanna Birke
Jazyk: Angličtina
Väzba: Brožovaná
Dostupnosť: Skladom u dodávateľa
Odosielame za 5-8 dní
50.18
Model-based recursive partitioning (MOB) provides a powerful synthesis between machine-learning insp...

Informácie o knihe

Autor
Jazyk
Angličtina
Väzba
Kniha - Brožovaná
Vydalo
2015
Stránok
240
EAN
9783658085049
ISBN
3658085045
Enbook ID
09136900
Hmotnosť
3451
Rozmery
148 x 210 x 213

Kompletný popis

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.

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