Tesis doctoral de Molanes López Elisa María
In this mongraph, kernel estimators of the relative density are presented and several global bandwidth selectors are designed to appropriately choose the smoothing parameter. in chapter 1 a more detailed introductrion to survival analysis, the bootstrap technique, nonparametric curve estimation, two sample problems and relative curves is given. the simplest case when the data are completely observed is studied in chapter 2. Several bandwidht selectors are designed for two kernel estimators of the relative density, based on plug-in ideas and the bootstrap technique. A simulation study presents some results where the behaviour of these anda a classical selector are compared. chapter 3 deals with the problem of estimating the relative density with right censores and left truncated data. Three bandwidth selectors are proposed for the relative density kernel estimator considered for this scenario, and their performance, under different percentages of censoring and truncation, is checked througn a simulation study. in chapter 4 a test for the null hypothesis of equal populations is designed using the relative distribution function via an empirical likelihood approach. finally, chapter 5 include two real data applications concerning prostate and gastricu cancer and chapter 6 collects some future research lines.
Datos académicos de la tesis doctoral «Nonparametric statistical inference for relative curves in two-sample problems«
- Título de la tesis: Nonparametric statistical inference for relative curves in two-sample problems
- Autor: Molanes López Elisa María
- Universidad: A coruña
- Fecha de lectura de la tesis: 30/03/2007
Dirección y tribunal
- Director de la tesis
- Ricardo Cao Abad
- Tribunal
- Presidente del tribunal: wenceslao González manteiga
- ingrid Van keilegom (vocal)
- noel Veraverbeke (vocal)
- kenneth Hess (vocal)