 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, 17.8.2000
