WOMBAT – A program for Mixed Model Analyses by Restricted Maximum Likelihood

FAQ: Error messages

Crash "Segmentation fault"

  • Q: WOMBAT crashes with a “Segmentation fault” with a heap of unintelligible numbers to follow – this seems to happen quite early on, i.e. during the set-up phase before any likelihoods are printed to the screen. What is wrong?
  • A: Long answer on separate page – here

Message "Small/Invalid Pivot"

  • Q: When I run WOMBAT I sometimes get a message to the screen, saying either small, negative or invalid pivot - What does it mean and what should I do about it?
  • A: Long answer on separate page – here

Message "lnkloc" : dimension exceeded !!

  • Q: WOMBAT stops with this error message – why does this occur and, more importantly, is there anything I can do to make this go away (other than reducing the size of my analysis)?
  • A: Depending on what exactly you are trying to do, this message can appear in different parts of the program – it is basically a 'safety catch' making sure your analysis has enough room. Most arrays needed are allocated at exactly the size required for the analysis; however, in some spots WOMBAT guesses at the space needed and, occasionally, this guess is simply wrong. In addition, there are some hard-coded maximum values and if your model of analysis is very big it may exceed one of these values.
    1. The first place this message may occur is during calculation of the inverse of the numerator relationship matrix (I have never seen this happen though); if it does, you are likely to have a very big and very dense pedigree and would be best advised to reduce the size of your analysis.
    2. The second possibility is that you are trying to use the PX-EM algorithm (this is the default for the first few iterates when there are more than 18 parameters to be estimated, so you may be doing this without having explicitly chosen to do so), and WOMBAT stops before the first iterate. WOMBAT has a guess on how many non-zero off-diagonal elements there are in one triangle of the coefficient matrix of the mixed model equations and then attempts to set this up and to determine the actual number. If this is too small, it will stop. A particular scenario when this has been found to occur it the case of an analysis trying to estimate a covariance matrix of reduced rank (option PC), where the rank is substantially less than the dimension of the matrix.
      To get around this, you could try to:
      • use the AI-REML algorithm from the start (see run time option —-aireml), especially if you have good starting values
      • set the initial guess manually using the run time option —-choozhz
    3. The third place this can happen is when using the iterative solutions module; again, setting the maximum number manually via the —-choozhz option may help.
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