/* * Copyright (C) 2006 Filip Borowicz * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 59 Temple Place, Suite 330, Boston, * MA 02111-1307 USA */ /** * Robustly estimates the baseline cumulative hazard * * @parma exp(beta'z) * @parma the vector of times * @parma the vector of censoring indicators * @parma the exp(prev_beta'z) (prev_beta - beta obatined through previous step) * @parma the M value * @parma the number of individuals * @parma the type of weighting function * @parma the robustly estimated baseline cumulative hazard * * @return void */ #include "coxrobust.h" void lambda(double *exp_zbeta, double *time, int *status, double *prev_exp_zbeta, double *M, int *n_row, int *a_type, double *lmb) { int i, k; double a_ii, sum; WEIGHT_FUNCTION A; A = get_weight_function(*a_type); for (i=0; i<*n_row; i++) { if ( status[i] != 0 ) { a_ii = A(time[i], prev_exp_zbeta[i], *M); if ( a_ii > 0 ) { sum = 0; for (k=i; k<*n_row; k++) { sum += A(time[i], prev_exp_zbeta[k], *M) * exp_zbeta[k]; } lmb[i] = (i == 0) ? a_ii/sum : lmb[i-1] + a_ii/sum; } else { lmb[i] = (i == 0) ? 0 : lmb[i-1]; } } else { lmb[i] = (i == 0) ? 0 : lmb[i-1]; } } }