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PyIBS

  • Installation
  • Getting started
  • PyIBS: Frequently Asked Questions
  • Examples
    • PyIBS Example 1: Basic usage and calibration
    • PyIBS Example 2: Maximum-likelihood estimation with PyBADS
    • PyIBS Example 3: Posterior and model evidence with PyVBMC
  • Documentation
    • IBS
    • EstimateResult
    • Classes
      • IBS
      • EstimateResult
      • IBSSamplingError
    • Functions
      • ibs_basic
      • check_for_updates
  • Instructions for developers and contributors
  • About us
  • Repository
  • Open issue

Index

_ | A | C | D | E | I | M | N | R | S | V

_

  • __call__() (pyibs.IBS method)

A

  • acceleration (pyibs.IBS property)
  • acceleration_threshold (pyibs.IBS property)

C

  • check_for_updates() (in module pyibs)

D

  • design_matrix (pyibs.IBS property)

E

  • EstimateResult (class in pyibs)

I

  • IBS (class in pyibs)
  • ibs_basic() (in module pyibs)
  • IBSSamplingError

M

  • max_iter (pyibs.IBS property)
  • max_mem (pyibs.IBS property)
  • max_samples (pyibs.IBS property)
  • max_time (pyibs.IBS property)

N

  • neg_logl_threshold (pyibs.IBS property)
  • num_samples_per_call (pyibs.IBS property)

R

  • response_matrix (pyibs.IBS property)

S

  • sample_from_model (pyibs.IBS property)

V

  • vectorized (pyibs.IBS property)
  • vectorized_threshold (pyibs.IBS property)

© Copyright 2026, Machine and Human Intelligence research group (PI: Luigi Acerbi, University of Helsinki).

PyIBS is one of the open-source model-fitting tools from the Machine and Human Intelligence Group at the University of Helsinki.