anchor.diff:  
   end module nsb_mod
   
  -subroutine plugin(n,counts,estimate)
  +subroutine plugin(n, counts, estimate)
     ! plugin estimator - no prior, no regularization
     use constants
     use counter
  
positive.code:   call counts_reset()
  
  end subroutine plugin
  
  subroutine pseudo(n,counts,nc,alpha,estimate)
    ! pseudocount estimator(s)
  
negative.code: 
  end subroutine pseudo
  
  subroutine pseudo_from_multiplicities(n, nk1, zk1, nc, alpha, estimate)
    ! pseudo counts
    use constants
    use counter
    implicit none
  
    integer, intent(in) :: n
    integer, intent(in) :: nk1(n)
    integer, intent(in) :: zk1(n)
    real(float64), intent(in)  :: nc
    real(float64),   intent(in)  :: alpha
    real(float64), intent(out) :: estimate
  
    integer :: i
    real(float64)   :: ni, na
  
    call counts_fit(nk1, zk1)
  
    call add_empty_bins(nc)
  
    estimate = 0.0_float64
    do i = 1,size(nk)
       ni = nk(i) + alpha
       estimate = estimate - zk(i)*ni*log(ni)
    end do
    na = nc * alpha
    estimate = estimate / (n_data + na) + log(n_data + na)
  
    call counts_reset()
  
  end subroutine pseudo_from_multiplicities
  
  subroutine ww(n, counts, nc, alpha, estimate, err_estimate)
    ! posterior mean entropy (averaged over Dirichlet distribution) given alpha
    use constants
  