I'm fitting a zero-inflated poisson model using the "pscl" package. The formula that I'm using is:


But then I get this message:

Error in solve.default(as.matrix(fit$hessian)) : system is computationally singular: reciprocal condition number = 2.33459e-20

I saw in other forums that the problem may be related to my data. Is that correct?


2 Answers 2


From another post (here: Error "system is computationally singular" when running a glm), and based on the number of predictor variables you have in your model, I would suggest you look for collinear predictors in your model, or whether you are trying to fit a model with more variables than observations.


I'm not sure how much similarity there in the errors but I get the error below using hurdle().

Error in solve.default(as.matrix(fit_zero$hessian)) : 
  Lapack routine dgesv: system is exactly singular: U[1,1] = 0

In my case, the error happens only when I specify the weights=weight_var. Using a normalized weight (weights= weight_var/mean(weight_var)) solved my problem.


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