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