Kernel Estimation of Conditional Hazard Function for  Cancer
Data

D 2014

Kernel Estimation of Conditional Hazard Function for Cancer Data

SELINGEROVÁ, Iveta, Ivanka HOROVÁ and Jiří ZELINKA

Basic information

Original name

Kernel Estimation of Conditional Hazard Function for Cancer Data

Name in Czech

Jádrové odhady podmíněné rizikové funkce pro rakovinová data

Authors

SELINGEROVÁ, Iveta (203 Czech Republic, guarantor, belonging to the institution), Ivanka HOROVÁ (203 Czech Republic, belonging to the institution) and Jiří ZELINKA (203 Czech Republic, belonging to the institution)

Edition

1. vyd. Tenerife, Španělsko, Recent Advances in Energy, Environment, Biology and Ecology, p. 33-39, 7 pp. 2014

Publisher

WSEAS Press

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10103 Statistics and probability

Country of publisher

Spain

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

URL

RIV identification code

RIV/00216224:14310/14:00074903

Organization unit

Faculty of Science

ISBN

978-960-474-358-2

Keywords in English

Hazard function; kernel; bandwidth; cross-validation method; survival function; censoring

Změněno: 27/4/2015 14:22, Ing. Andrea Mikešková

Abstract

V originále

The hazard function is a useful tool in survival analysis and reflects the instantaneous probability that an individual will die within the next time instant. In practice, the hazard function depends on covariates as an age and a gender. The most frequently used method to estimate a conditional hazard function is semiparametric model suggested by D. R. Cox. Assumptions of this model are too restrictive in many cases. In the present paper is proposed an estimator for conditional hazard function as the ratio of kernel estimators for the onditional density and survival function. We illustrate the utility of the proposed method through application to cancer data sets.

Citovat

SELINGEROVÁ, Iveta, Ivanka HOROVÁ and Jiří ZELINKA. Kernel Estimation of Conditional Hazard Function for Cancer Data. In Vincenzo Niola. Recent Advances in Energy, Environment, Biology and Ecology. 1st ed. Tenerife, Španělsko: WSEAS Press, 2014, p. 33-39. ISBN 978-960-474-358-2.

@inproceedings{1159447,
   author = {Selingerová, Iveta and Horová, Ivanka and Zelinka, Jiří},
   address = {Tenerife, Španělsko},
   booktitle = {Recent Advances in Energy, Environment, Biology and Ecology},
   edition = {1.},
   editor = {Vincenzo Niola},
   keywords = {Hazard function; kernel; bandwidth; cross-validation method; survival function; censoring},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Tenerife, Španělsko},
   isbn = {978-960-474-358-2},
   pages = {33-39},
   publisher = {WSEAS Press},
   title = {Kernel Estimation of Conditional Hazard Function for Cancer Data},
   url = {http://www.google.cz/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&sqi=2&ved=0CDQQFjAB&url=http%3A%2F%2Fwww.wseas.us%2Fbooks%2F2010%2FCambridge%2FEE.pdf&ei=-MbXUoS3AefgygPPvYDABA&usg=AFQjCNHWU0JL2ynkTAX-FLuET2h9wLM7rg&sig2=w7NY0ORsFF3I-zO1oBC1uQ&bvm=b},
   year = {2014}
}

TY  - JOUR
ID  - 1159447
AU  - Selingerová, Iveta - Horová, Ivanka - Zelinka, Jiří
PY  - 2014
TI  - Kernel Estimation of Conditional Hazard Function for Cancer Data
PB  - WSEAS Press
CY  - Tenerife, Španělsko
SN  - 9789604743582
KW  - Hazard function
KW  - kernel
KW  - bandwidth
KW  - cross-validation method
KW  - survival function
KW  - censoring
UR  - http://www.google.cz/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&sqi=2&ved=0CDQQFjAB&url=http%3A%2F%2Fwww.wseas.us%2Fbooks%2F2010%2FCambridge%2FEE.pdf&ei=-MbXUoS3AefgygPPvYDABA&usg=AFQjCNHWU0JL2ynkTAX-FLuET2h9wLM7rg&sig2=w7NY0ORsFF3I-zO1oBC1uQ&bvm=b
L2  - http://www.google.cz/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&sqi=2&ved=0CDQQFjAB&url=http%3A%2F%2Fwww.wseas.us%2Fbooks%2F2010%2FCambridge%2FEE.pdf&ei=-MbXUoS3AefgygPPvYDABA&usg=AFQjCNHWU0JL2ynkTAX-FLuET2h9wLM7rg&sig2=w7NY0ORsFF3I-zO1oBC1uQ&bvm=b
N2  - The hazard function is a useful tool in survival analysis and reflects the instantaneous probability that an individual will die within the next time instant. In practice, the hazard function depends on covariates as an age and a gender. The most frequently used method to estimate a conditional hazard function is semiparametric model suggested by D. R. Cox. Assumptions of this model are too restrictive in many cases. In the present paper is proposed an estimator for conditional hazard function as the ratio of kernel estimators for the onditional density and survival function. We illustrate the utility of the proposed method through application to cancer data sets.
ER  -

SELINGEROVÁ, Iveta, Ivanka HOROVÁ and Jiří ZELINKA. Kernel Estimation of Conditional Hazard Function for Cancer Data. In Vincenzo Niola. \textit{Recent Advances in Energy, Environment, Biology and Ecology}. 1st ed. Tenerife, Španělsko: WSEAS Press, 2014, p.~33-39. ISBN~978-960-474-358-2.

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