# Covariance matrix in R with non-numeric variables

I am modeling a Gaussian distribution for a computational biology application, and I am working in the statistical package "R". In this regard, my problem is that I have to construct a covariance matrix with variables (non-numeric) and the covariance matrix is to be used in an maximizers of the likelihood function to predict the variables in the matrix.

I am unable to do that because I do not have an idea of how to construct a covariance matrix with non-numeric variable in the matrix.

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Can you clarify what you mean by "non-numeric" variables? Categorical (ordered?)? –  naught101 May 18 '12 at 5:06
One-up on the clarification. The covariance is defined as $\sum^n_{i=1}(x_{1i} - \bar{x}_1)(x_{2i}-\bar{x}_2)$, so the covariance of a non-numeric variable doesn't even exist. You could create a matrix of probabilities, though. –  gmacfarlane May 18 '12 at 11:40