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Více informací o knize Nonparametric Mean Preservation in Censored Regression

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• Anotace
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Anotace knihy

The aim of this book is to estimate the conditional §mean of some functions depending on the response §variable Y (moments, distributions...) in regression §models where this response is possibly censored. In §parametric regression, polynomial and nonlinear §conditional means are estimated in a new way while, §in nonparametric regression, some new estimators are §provided to approximate general L-functionals §(conditional mean, trimmed mean, quantiles...). The §ideas developed in those methods lead to establish §more general results in nonparametric estimation of §the conditional mean of functions depending on Y and §other variables and where the response can follow §other schemes of incomplete data (not only censored §but also missing or length-biased data). For each §procedure, asymptotic properties are established §while finite sample behavior is studied via §simulations. Examples from a variety of areas §highlight the interest of using the proposed §methodologies in practice.

Parametry knihy

• Plný název: Nonparametric Mean Preservation in Censored Regression
• Podnázev: Using Preliminary Nonparametric Smoothing to Make Inference in Censored Regression
• Autor: Cédric Heuchenne
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 180
• EAN: 9783836463911
• ID: 06960483
• Nakladatelství: VDM Verlag Dr. Müller
• Hmotnost: 284 g
• Rozměry: 220 × 150 × 11 mm
• Rok vydání: 2009

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