Loess with missing values

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Can you please open an issue for this in Loess.jl as I also think requiring AbstractFloat eltype is a bit cumbersome.

As a small comment: your code will not work when x has missing value as predict fail I think (not tested).

What I typically do is the following:

using DataFrames
function loess4Miss(x, y; span=0.3)  
  df = dropmissing(DataFrame(x=x, y=y, copycols=false), :y)
  model = loess(df.x, df.y; span=span, degree=1)
  predict(model, x)
end

(in general working on multiple columns is usually easier when using DataFrames.jl)

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