These are formatted summary files to be read (rather than processed by other programs). They have the extension .out.

If a pedigree file is specified, this file gives some summary statistics on the pedigree information found.

This file gives a summary about the model of analysis specified and the corresponding features of the data found. Statistics given include means, standard deviations and ranges for traits and covariables, and numbers of levels found for the effects in the model of analysis.

It is written after the first processing of the input files, i.e. during the set-up steps.

This files provides estimates of the parameters as estimated, and the resulting covariance matrices and their eigenvalues and, for reduced rank analyses, the corresponding matrices of eigenvectors. WOMBAT also writes out the corresponding matrices of correlations and variance ratios. In addition, values for any user-defined functions of covariances (see 4.11) are written out.

If the final estimates were obtained using the AI algorithm, WOMBAT provides approximate sampling errors for the parameters and covariance components estimated, as given by the inverse of the respective average information matrices. In addition, sampling errors of variance ratios and correlations are derived, as described in A.4.2.

This is an abbreviated version of SumEstimates.out, written out when the command line option --best is specified. It gives matrices of estimates pertaining to the set of parameters with the highest likelihood found so far.

This file lists the generalised least-squares solutions for all fixed effects fitted, together with ‘raw’ means and numbers of observations for individual subclasses.

HINT: If this file is the ‘by-product’ of an estimation run using the
AI-REML algorithm (default), no standard errors for fixed effects are
given. The reason is that the AI algorithm does not involve calculation
of the inverse of the coefficient matrix of the mixed model equations.
Asymptotic lower bound standard errors are written out, however, if the
(PX-)EM algorithm is used in the last iterate performed, or if a BLUP
run is specified, as both evaluate this inverse. Hence, to obtain standard
errors, carry out one iterate using the EM algorithm and specifying a
continuation run:

wombat -c –emalg1 parfile.par

(replacing parfile.par by the name of your parameter file). This also
provides a check on convergence - the increase in from the EM step
should be very small. Note though that for large and very large problems,
the EM iterate can require substantially longer (CPU time) than the AI
algorithm. Alternatively, specify a BLUP run:

wombat -c –blup parfile.par

Again, note that the latter does not involve pruning of the pedigree,
i.e. WOMBAT will recalculate the inverse of the numerator relationship
matrix and owerwrite the existing file(s) nrminvḃin.

This file is only written out when specifying run option --sample (see 5.2.9. It gives a brief summary of the characteristics of the analysis and average information matrix for which samples were obtained, together with means and variances across replicates. In addition, large deviations between theoretical results from the information matrix and samples obtained are flagged.