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@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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