Hi,
You did a really good job providing a reproducible example, except
that you didn't mention which package sem() comes from. (sem, I'm
assuming).
I don't know how you came up with your covariance matrix, but it
*isn't* symmetric:
> isSymmetric(S.Seed.BB)
[1] FALSE
> S.Seed.BB[6, 2]
[1] 37.758
Hello, I tried to do a 'sem' analysis for data of how blueberry consumption
by birds is influenced by a pollution gradient, using distance and
vegetation structural and composition variables, but I got the following
error message:
Error in sem.default(ram = ram, S = S, N = N, param.names = pars, v
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