scalanlp/breeze

Numpy parity: statistics fitting

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#217 opened on Apr 9, 2014

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 (1 comment) (0 reactions) (0 assignees)Scala (3,453 stars) (690 forks)batch import
help wantedproject

Description

Numpy gives the fit function, letting you input data and get a distribution as output. Would be nice to have that.

  • chisquare
  • f
  • gumbel
  • hypergeometric
  • laplace
  • lognormal
  • logseries
  • multivariate_normal
  • noncentral_chisquare
  • noncentral f
  • pareto
  • power
  • rayleigh
  • student's t
  • triangular
  • wald
  • weibull
  • zipf

Contributor guide

Tech stack
scala
Domain
data
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
over 1 week
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
needs investigation
Prerequisites
Scalastatistics
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
20
Research direction
This issue requests adding fit functions for multiple probability distributions. Start by examining numpy's implementation (e.g., scipy.stats) and Breeze's existing distribution classes in breeze.stats. A good first step is to implement one distribution (e.g., normal) to understand the pattern. The checklist provides specific distributions to target.