Publication details

Kernel Estimation of Conditional Hazard Function for Cancer Data

Authors

SELINGEROVÁ Iveta HOROVÁ Ivanka ZELINKA Jiří

Year of publication 2014
Type Article in Proceedings
Conference Recent Advances in Energy, Environment, Biology and Ecology
MU Faculty or unit

Faculty of Science

Citation
Web 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
Field Applied statistics, operation research
Keywords Hazard function; kernel; bandwidth; cross-validation method; survival function; censoring
Description 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.