Displaying 1 to 8 from 8 results

node-stats-lite - A light statistical package that operates on Arrays.

  •    Javascript

A fairly light statistical package. Works with numeric arrays, and will automatically filter out non-numeric values and attempt to convert string numeric values. All of the exported functions take vals which is an array of numeric values. Non-numeric values will be removed, and string numbers will be converted to Numbers.

tdigest - tdigest: javascript implementation of Dunning's T-Digest for streaming quantile approximation

  •    Javascript

The T-Digest is a data structure and algorithm for constructing an approximate distribution for a collection of real numbers presented as a stream. The algorithm makes no guarantees, but behaves well enough in practice that implementations have been included in Apache Mahout and ElasticSearch for computing summaries and approximate order statistics over a stream. For an overview of T-Digest's behavior, see Davidson-Pilon's blog post regarding a python implementation. For more details, there are the tdigest paper and reference implementation (Java). This javascript implementation is based on a reading of the paper, with some boundary and performance tweaks.

stata-gtools - Faster implementation of Stata's collapse, egen, xtile, isid, and more using C plugins

  •    Stata

Faster Stata for big data. This packages provides a hash-based implementation of collapse, pctile, xtile, contract, egen, isid, levelsof, duplicates, and unique/distinct using C plugins for a massive speed improvement. This package's aim is to provide a fast implementation of various Stata commands using hashes and C plugins. If you plan to use the plugin extensively, check out the remarks below and the FAQs for caveats and details on the plugin (including some extra features!).

tdigest - An implementation of Ted Dunning's t-digest in Go.

  •    C++

This is an implementation of Ted Dunning's t-digest in Go. The implementaion is based off Derrick Burns' C++ implementation.

redis-tdigest - t-digest module for Redis

  •    C

This is a Redis module for the t-digest data structure which can be used for accurate online accumulation of rank-based statistics such as quantiles and cumulative distribution at a point. The implementation is based on the Merging Digest implementation by the author. Before going ahead, make sure that the Redis server you're using has support for Redis modules.

tdigest - t-Digest data structure in Python

  •    Python

This is a Python implementation of Ted Dunning's t-digest data structure. The t-digest data structure is designed around computing accurate estimates from either streaming data, or distributed data. These estimates are percentiles, quantiles, trimmed means, etc. Two t-digests can be added, making the data structure ideal for map-reduce settings, and can be serialized into much less than 10kB (instead of storing the entire list of data). tdigest is compatible with both Python 2 and Python 3.