anchor.diff:                  endif
                   
               elseif (options%analog_regression) then
  -                call CPU_TIME(inner_timeone)
  -                call CPU_TIME(timeone)
  +                call System_Clock(timeone)
                   analogs = find_analogs(predictor(i,:), atm, n_analogs)
                   do a=1,n_analogs
                       obs_analogs(a) = obs(analogs(a))
                       regression_data(a,:) = atm(analogs(a),:)
                   enddo
  -                call CPU_TIME(timetwo)
  +                call System_Clock(timetwo)
                   timers(1) = timers(1) + (timetwo-timeone)
   
  -                call CPU_TIME(timeone)
  +                call System_Clock(timeone)
                   output(i) = compute_regression(predictor(i,:), regression_data, obs_analogs, coefficients, errors(i))
                   output_coeff(1:nvars,i) = coefficients
  -                call CPU_TIME(timetwo)
  +                call System_Clock(timetwo)
                   timers(2) = timers(2) + (timetwo-timeone)
   
  -                call CPU_TIME(timeone)
  +                call System_Clock(timeone)
                   if (logistic_threshold/=kFILL_VALUE) then
                       if (options%logistic_from_analog_exceedance) then
                           
                           ! if the user specified using fewer analogs specifically for the logistic component, find them here
                           if (options%n_log_analogs /= n_analogs) then
                               analogs(1:options%n_log_analogs) = find_analogs(predictor(i,:), atm, options%n_log_analogs)
  -                            call CPU_TIME(timetwo)
  +                            call System_Clock(timetwo)
                               timers(9) = timers(9) + (timetwo-timeone)
                               
  -                            call CPU_TIME(timeone)
  +                            call System_Clock(timeone)
                               logistic(i) = compute_analog_exceedance(obs, analogs(1:options%n_log_analogs), logistic_threshold)
                           else
                               logistic(i) = compute_analog_exceedance(obs, analogs, logistic_threshold)
  
positive.code:                             ! save these data for output debugging / algorithm development while we are at it. 
                              output%variables(1)%predictors(:,i,j,v+1) = pred_data( p_start   : p_end,    v+1)
                              output%variables(1)%training  (:,i,j,v+1) = train_data(t_tr_start: t_tr_stop,v+1)
                          enddo
  
                          do v=1,n_obs_variables
  
negative.code:         real,    dimension(:),   intent(inout):: logistic
          real,                    intent(in)   :: logistic_threshold
          type(config),            intent(in)   :: options
          integer*8, dimension(:), intent(inout) :: timers
          
          real,    dimension(:),   allocatable :: output
          real,    dimension(:),   allocatable :: obs_analogs
  