Welcome!

OnlineStats does statistics and data visualization for big/streaming data via online algorithms. Each algorithm:

1. processes data one observation at a time.
2. uses O(1) memory.

Basics

1) Creating

• Stats are subtypes of OnlineStat{T} where T is the type of a single observation.

julia> using OnlineStats
julia> m = Mean()Mean: n=0 | value=0.0
julia> supertype(Mean)OnlineStat{Number}

2) Updating

• Stats can be updated with single or multiple observations e.g. fit!(m, 1) and fit!(m, [1,2,3]).

julia> y = randn(100);
julia> fit!(m, y)Mean: n=100 | value=-0.00382867
julia> value(m)-0.003828666091082929

3) Merging

• Stats can be merged.

julia> y2 = randn(100);
julia> m2 = fit!(Mean(), y2)Mean: n=100 | value=0.00779837
julia> merge!(m, m2)Mean: n=200 | value=0.00198485