streamly-statistics: Statistical measures for finite or infinite data streams.

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Statistical measures for finite or infinite data streams.

All operations use numerically stable floating point arithmetic. Measurements can be performed over the entire input stream or on a sliding window of fixed or variable size. Where possible, measures are computed online without buffering the input stream.

Includes:

  • Summary: length, sum, powerSum

  • Location: minimum, maximum, rawMoments, means, exponential smoothing

  • Spread: range, variance, deviations

  • Shape: skewness, kurtosis

  • Sample statistics, resampling

  • Probablity distribution: frequency, mode, histograms

  • Transforms: Fast fourier transform


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Versions [RSS] 0.1.0, 0.2.0
Change log CHANGELOG.md
Dependencies base (>=4.9 && <5), containers (>=0.5 && <0.9), deque (>=0.4.4 && <0.4.5), mwc-random (>=0.15 && <0.16), random (>=1.2 && <1.4), streamly-core (>=0.3.0 && <0.4.0) [details]
Tested with ghc ==8.8.4, ghc ==8.10.7, ghc ==9.2.7, ghc ==9.4.4, ghc ==9.6.3, ghc ==9.8.1, ghc ==9.10.1, ghc ==9.12.1, ghc ==9.14.1
License Apache-2.0
Copyright 2019 Composewell Technologies
Author Composewell Technologies
Maintainer streamly@composewell.com
Uploaded by adithyaov at 2025-09-22T13:26:24Z
Revised Revision 1 made by harendra at 2026-04-17T07:16:18Z
Category Streamly, Statistics, Streaming
Home page https://streamly.composewell.com
Bug tracker https://github.com/composewell/streamly-statistics/issues
Source repo head: git clone https://github.com/composewell/streamly-statistics
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Downloads 152 total (6 in the last 30 days)
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Readme for streamly-statistics-0.2.0

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streamly-statistics

Statistical measures for finite or infinite data streams.

All operations use numerically stable floating point arithmetic. Measurements can be performed over the entire input stream or on a sliding window of fixed or variable size. Where possible, measures are computed online without buffering the input stream.

Includes:

  • Summary: length, sum, powerSum
  • Location: minimum, maximum, rawMoments, means, exponential smoothing
  • Spread: range, variance, deviations
  • Shape: skewness, kurtosis
  • Sample statistics, resampling
  • Probablity distribution: frequency, mode, histograms
  • Transforms: Fast fourier transform