  A weighted random survival forest is presented in the paper. It can be
regarded as a modification of the random forest improving its performance. The
main idea underlying the proposed model is to replace the standard procedure of
averaging used for estimation of the random survival forest hazard function by
weighted avaraging where the weights are assigned to every tree and can be
veiwed as training paremeters which are computed in an optimal way by solving a
standard quadratic optimization problem maximizing Harrell's C-index. Numerical
examples with real data illustrate the outperformance of the proposed model in
comparison with the original random survival forest.
