Missing values support

I tested out this package on 0.7 with `missings` and got the following error:

I think this is because `Statistics` is not imported by `NaNMath`, so the function calls to `NaNMath.mean` can't fall base on `Statistics.mean`.

I think the solution here is to add `import Statistics` and add fall backs for operations of type `Any` so those are called when there are missing values. Does that seem feasible?

```
nm.mean([1.,2., missing])
> ERROR: WARNING: Base.mean is deprecated: it has been moved to the standard library package `Statistics`.
Add `using Statistics` to your imports.
in module Base
MethodError: no method matching mean(::Array{Union{Missing, Float64},1})
You may have intended to import Base.mean
Closest candidates are:
mean(::AbstractArray{T<:AbstractFloat,N} where N) where T<:AbstractFloat at /Users/peterdeffebach/.julia/packages/NaNMath/pEda/src/NaNMath.jl:167
Stacktrace:
[1] top-level scope at none:0
```

Start in NaNMath.jl around the mean implementation at line 167 and review how Statistics.mean is imported and how calls on arrays containing missing are dispatched. Reproduce the reported nm.mean([1., 2., missing]) failure, then verify that the intended fallback behavior works for missing-valued inputs.

Written by the indexing model from the issue text.