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Kernel Estimation of Conditional Hazard Function for Cancer Data

Název česky Jádrové odhady podmíněné rizikové funkce pro rakovinová data
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SELINGEROVÁ Iveta HOROVÁ Ivanka ZELINKA Jiří

Rok publikování 2014
Druh Článek ve sborníku
Konference Recent Advances in Energy, Environment, Biology and Ecology
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
www 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
Obor Aplikovaná statistika, operační výzkum
Klíčová slova Hazard function; kernel; bandwidth; cross-validation method; survival function; censoring
Popis 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.