python-pypsignifit – psychometric analysis of psychophysics data in Python

Psignifit allows fitting of psychometric functions to datasets while maintaining full control over a large number of parameters. Psignifit performs the calculation of confidence intervals as well as goodness-of-fit tests. In addition it offers:

  • full Bayesian treatment of psychometric functions including Bayesian model selection and goodness of fit assessment
  • identification of influential observations and outlier detection
  • flexible shape definition of the psychometric function

This package provides the Python bindings.

Package availability chart
Distribution Base version Our version Architectures
Debian GNU/Linux 6.0 (squeeze)   3.0~beta.20120611.1-1~nd60+1 i386, amd64
Debian GNU/Linux 7.0 (wheezy) 3.0~beta.20120611.1-1 3.0~beta.20120611.1-1~nd70+1 i386, amd64
Debian GNU/Linux 8.0 (jessie) 3.0~beta.20120611.1-1 3.0~beta.20120611.1-1~nd70+1 i386, amd64
Debian GNU/Linux 9.0 (stretch)   3.0~beta.20120611.1-1~nd70+1+nd90+1 i386, amd64
Debian unstable (sid)   3.0~beta.20120611.1-1~nd+1 i386, amd64
Ubuntu 12.04 LTS “Precise Pangolin” (precise)   3.0~beta.20120611.1-1~nd12.04+1 i386, amd64
Ubuntu 14.04 “Trusty Tahr” (trusty) 3.0~beta.20120611.1-1build1 3.0~beta.20120611.1-1~nd12.04+1+nd12.10+1+nd13.04+1+nd13.10+1+nd14.04+1 i386, amd64

Comments

blog comments powered by Disqus