Local Variance Estimation for Uncensored and Censored Observations, 1st Edition

  • Published By:
  • ISBN-10: 3658023147
  • ISBN-13: 9783658023140
  • DDC: 519.5
  • Grade Level Range: College Freshman - College Senior
  • 130 Pages | eBook
  • Original Copyright 2013 | Published/Released June 2014
  • This publication's content originally published in print form: 2013

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Paola Gloria Ferrario develops and investigates several methods of nonparametric local variance estimation. The first two methods use regression estimations (plug-in), achieving least squares estimates as well as local averaging estimates (partitioning or kernel type). Furthermore, the author uses a partitioning method for the estimation of the local variance based on first and second nearest neighbors (instead of regression estimation). Approaching specific problems of application fields, all the results are extended and generalised to the case where only censored observations are available. Further, simulations have been executed comparing the performance of two different estimators (R-Code available!). As a possible application of the given theory the author proposes a survival analysis of patients who are treated for a specific illness.

Table of Contents

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
Other Frontmatter.
Deutsche Zusammenfassung.
List of Figures.
List of Abbreviations.
1: Introduction.
2: Least Squares Estimation via Plug-In.
3: Local Averaging Estimation via Plug-In.
4: Partitioning Estimation via Nearest Neighbors.
5: Local Variance Estimation for Censored Observations.
6: Simulations.