sprand as samples from sparse distribution

I was thinking, in the spirit of this package, maybe `rand(Normal(),SparseMatrixCSC,p,m,n) ` could be better expressed as `rand(Bernoulli(p,Normal()),SparseMatrixCSC,m,n)` where `Bernoulli(p, Normal())` would be the "Gauss-Bernoulli" or "Spike-and-Slab" mixture distribution

P(x) = (1-p) delta(x)+ p Normal(x)

It seems to make things a bit more generic.

No files or tests are named. Start by locating the current rand(Normal(), SparseMatrixCSC, p, m, n) entry point and reviewing how Bernoulli(p, Normal()) would represent the proposed sparse distribution; done means the API and resulting behavior are agreed and implemented.

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