 Usage:  {betahat, betak, ck} = hazbeta(data, {maxit})  

 

 Input:



  data                   n x (p+4) matrix, the first column is the sorted 

                         survival time t, followed by the sorted delta, 

                         inidcating if censoring has occured, labels l, a 

                         column containing the number of ties, and lastly, 

                         the sorted covariate matrix z. 

                         

  maxit                  scalar, maximum number of iteration for the 

                         Newton-Raphson procedure, default = 40. 

                         

 Output:



  betahat                p x 1 vector, estimate of the regression 

                         parameter beta 

                         

  betak                  maxit x p matrix, parameter values through the 

                         Newton-Raphson procedure 

                         

  ck                     maxit x 1 vector, convergence criteria values 

                         through the Newton-Raphson procedure 

                         

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(C) MD*TECH Method and Data Technologies, 21.9.2000

