Hello everyone,

I am want to do something conceptually simple using MATLAB.jl package. I have a BigFloat matrix in Julia, and I want to send to Matlab to compute its inverse/determinant/eigenvalues with arbitrary-precision arithmetic (vpa) and return back to Julia.

Assuming that Matlab is already in local PATH, the following example should work:

```
using MATLAB
using LinearAlgebra
using GenericLinearAlgebra
m = n = 2
a = rand(m, n)
x = mxarray(a)
# works OK
inv(a)
mat"inv($x)"
det(a)
mat"det($x)"
eigen(a)
mat"eig($x)"
# NOT OK with big numbers
b = big.(a)
y = mxarray(b)
# Maybe a better way to write it could be
# mat"y = vpa($b,60)"
det(b)
mat"det($y)" # returns: Undefined function 'det' for input arguments of type 'cell'.
eigen(b) # ? how to make it work ?
mat"eig($y)" # returns a bigger message complaining about types
```

By the error messages I guess that MATLAB.jl convert Julia type in some data structure, and send to Matlab to be executed. Any ideas of how to handle my example with BigFloat ?

Thank you