We propose a robust Cox regression model with outliers. The model is fit by trimming the smallest contributions to the partial likelihood. To do so, we implement a Metropolis-type maximization routine, and show its convergence to a global optimum. We discuss global robustness properties of the approach, which is illustrated and compared through simulations. We finally fit the model on an original and on a benchmark data set.
Robust estimation for the Cox regression model based on trimming / Farcomeni, Alessio; Sara, Viviani. - In: BIOMETRICAL JOURNAL. - ISSN 0323-3847. - STAMPA. - 53:6(2011), pp. 956-973. [10.1002/bimj.201100008]
Robust estimation for the Cox regression model based on trimming
FARCOMENI, Alessio;
2011
Abstract
We propose a robust Cox regression model with outliers. The model is fit by trimming the smallest contributions to the partial likelihood. To do so, we implement a Metropolis-type maximization routine, and show its convergence to a global optimum. We discuss global robustness properties of the approach, which is illustrated and compared through simulations. We finally fit the model on an original and on a benchmark data set.File allegati a questo prodotto
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
