WOMBAT calculates four different criteria to determine whether an analysis has converged. The first two are simple changes, available for all maximisation algorithms, the other two are based on the derivatives of the log likelihood function, i.e. can only be obtained for the AI algorithm. The criteria are :
 (A.1) 
where denotes the estimate of the th parameter from iterate , and is the number of parameters.
 (A.2) 
 (A.3) 
where is the the element of the inverse of the average information matrix for iterate . This gives a measure of the expected difference of from the maximum, and has been suggested as an alternative convergence criterion [2].

Default values for the thresholds for these criteria used in WOMBAT are summarised in Table A.1.
N.B.: Current values used are rather stringent; ‘softer’ limits combining several criteria may be more appropriate for practical estimation.