OnlineStats

Online Algorithms for Statistics, Models, and Big Data Viz

Online algorithms are well suited for streaming data or when data is too large to hold in memory. OnlineStats processes observations one by one and all algorithms use O(1) memory.

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Quickstart

import Pkg

Pkg.add("OnlineStats")

using OnlineStats

o = Series(Mean(), Variance(), P2Quantile(), Extrema())

fit!(o, randn(10^6))

Documentation

Contributing

When contributing to OnlineStats, trivial PRs like documentation typos are very welcome! For nontrivial changes, please first discuss the change you wish to make via issue/email/slack with @joshday.

Authors

• Primary Author: Josh Day (@joshday)
• Significant early contributions from Tom Breloff (@tbreloff)

See also the list of contributors to OnlineStats.

License

OnlineStats is licensed under the MIT License - see the LICENSE.md file for details.