Import of v7.1.2

Author: chmathys

COPYING

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+# HGF Toolbox
+Release ID: $Format:%h %d$
+
+--- 
+
+Copyright (C) 2012-2022 Christoph Mathys <[email protected]>
+Translational Neuromodeling Unit (TNU)
+University of Zurich and ETH Zurich
+
+---
+
+The HGF toolbox is free software: you can redistribute it and/or
+modify it under the terms of the GNU General Public License as
+published by the Free Software Foundation, either version 3 of the
+License, or (at your option) any later version.
+
+This program is distributed in the hope that it will be useful, but
+WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with this program (see the file COPYING).  If not, see
+<http://www.gnu.org/licenses/>.
+
+---
+
+## How to cite the HGF Toolbox
+Please cite the following paper when using the HGF Toolbox:
+
+Frässle, S., et al. (2021). TAPAS: An Open-Source Software Package for
+Translational Neuromodeling and Computational Psychiatry. Frontiers in
+Psychiatry, 12:680811. https://doi.org/10.3389/fpsyt.2021.680811
+
+
+## Installation
+
+Move this folder to a location of your choice and add it to your Matlab
+path.
+
+
+## Documentation and configuration
+
+Documentation can be found in the manual contained in the Manual.pdf
+file. This will point you to the relevant configuration files. Further
+documentation is available throughout the source code.
+
+
+## Tutorial demo
+
+There is a Matlab LiveScript tutorial demo that can be launched by
+opening hgf_demo.mlx in Matlab. A PDF version is available in
+hgf_demo.pdf.
+
+## Release notes
+
+### v7.1
+- Add ehgf_ar1_plotTraj
+- Bugfix
+### v7.0
+- Numerical stability improvements to optimization
+- Combined response models (more than one observation per trial)
+- Various bugfixes and minor improvements
+
+### v6.1
+- Improved functionality of beta_obs response model
+- Included reference to TAPAS paper
+
+### v6.0
+- Introduced first eHGF models (ehgf, ehgf_binary, ehgf_jget)
+- Enabled calling fitModel with config structures as arguments
+- Enabled changing config structures on the fly
+- Introduced sampleModel for sampling from the prior
+- Various other additions, improvements, and bugfixes
+
+### v5.3
+- Enabled setting and storing of seed for random number generator in simulations
+- Debugged reading of response model configuration in simModel
+- Reduced default maxStep from 2 to 1 in quasinewton_oqptim_config
+- Improved readability of siem files for unitsq_sgm and softmax_binary
+- Added simulation capability for softmax_wld and softmax_mu3_wld
+- Added softmax_wld response model
+- Improved readability of softmax_mu3_wld code
+- Improved readability of softmax and softmax_mu3 code
+
+### v5.2
+- Brought hgf_demo.pdf up to date
+- Added gaussian_obs_offset response model
+- Brought example in simModel up to date
+- Added sim and namep files for unitsq_sgm_mu3
+- Fixed typo in softmax_mu3_wld
+- Introduced softmax_mu3_wld decision model
+- Estimate mu0_2 by default in hgf_ar1_binary_mab
+- Improved comment in softmax_mu3_config
+- Change to pi_2 update in hgf_ar1_binary_mab
+- Enabled simulation for hgf_ar1_binary_mab
+- Added softmax_mu3
+- Added hgf_ar1_binary_mab
+- Fixed automatic detection of number of levels in hgf_ar1_binary
+- Fixed documentation of hgf_ar1_binary
+- Fixed hgf_binary_mab_plotTraj
+- Fixed trajectory calculations in hgf_binary_mab
+- Adapted riddersgradient and riddershessian to new Matlab versions
+- Quashed bug in rw_binary_dual found by [email protected]
+
+### v5.1
+- Added condhalluc_obs and condhalluc_obs2 models
+- Introduced kappa1 in all binary HGF models
+
+### v5.0
+- Ported interactive demo to Matlab LiveScript
+- Various additional small improvements
+- Updated manual
+- Updated and renamed README to README.md
+
+### v4.17
+- Improvements to logrt_linear_binary_minimal
+
+### v4.16
+- Added the binary HGF with trial-by-trial perceptual uncertainty as hgf_binary_pu_tbt
+
+### v4.15
+- Added the Kalman filter as kf
+
+### v4.14
+- Improved the beta_obs model
+- Improved calculation of implied 1st-level learning rate
+
+### v4.13
+- Corrected sign of update trajectories
+- Added option to base responses on predictions or posteriors in
+  the beta_obs model
+
+### v4.12
+- Added tapas_autocorr.m
+
+### v4.11
+- Predictions and residuals returned by all observations models
+- Added tapas_fit_plotResidualDiagnostics()
+
+### v4.10
+- Added hgf_categorical_norm
+- Added Boltzmann distribution (i.e., softmax normalization) as tapas_boltzmann()
+
+### v4.9
+- Set implied learning rate at first level to 0 if update is zero
+
+### v4.8
+- Give choice of using predictions or posteriors with softmax_binary
+
+### v4.7
+- Added cdfgaussian_obs model
+- Added hgf_binary_pu (perceptual uncertainty) model
+- Improvements for beta_obs with hgf_whichworld
+
+### v4.6
+- Adapted beta_obs to deal with ph_binary
+- Added Pearce-Hall in ph_binary
+- Clarified the role of default settings in comments of fitModel
+- Brought softmax_binary_sim up to date
+
+### v4.5
+- Improved comments in softmax_binary_sim
+- Improved comments in tapas_beta_obs.m
+- Added tapas_beta_obs_{sim,namep}.m
+
+### v4.4
+- Added tapas_hgf_ar1_binary_namep.m
+- Improved rw_binary
+
+### v4.3
+- Added bayes_optimal_categorical
+- Improved hgf_categorical_plotTraj
+
+### v4.2
+- Adapted softmax_sim to hgf_categorical
+- Added hgf_categorical
+- Added datagen_categorical and categorical data example
+
+### v4.1
+- Improved hgf_jget
+
+### v4.0
+- Added PDF manual
+- Added interactive demo in hgf_demo
+- Added file of raw commands from hgf_demo in hgf_demo_commands
+- Adapted fitModel to calculate AIC and BIC
+- Renamed F (negative variational free energy) to LME (log-model evidence, to
+  which it is an approximation)
+- Calculate accuracy and complexity in fitModel
+- Save everything relating to model quality under r.optim
+- Improved output of fitModel
+- Added hierarchical hidden Markov model (hhmm)
+- Added hidden Markov model (hmm)
+- Added WhatWorld (hgf_whatworld) model
+- Added linear log-reaction time (logrt_linear_whatworld) model for WhatWorld
+- Added WhichWorld (hgf_whichworld) model
+- Added AR(1) model for binary outcomes (hgf_ar1_binary)
+- Added Jumping Gaussian Estimation (hgf_jget) model
+- Added unitsq_sgm_mu3 decision model
+- Added binary multi-armed bandit model hgf_binary_mab
+- Added beta_obs observation model for decision noise on the unit interval
+- Added softmax decision model with different inverse temperature for each
+  kind of binary decision (softmax_2beta)
+- Added logrt_linear_binary decision model
+- Added Rescorla-Wagner model with different learning rate for each kind of
+  binary outcome (rw_binary_dual)
+- Included additional trajectories in output of hgf, hgf_ar1, hgf_ar1_mab,
+  hgf_binary, hgf_ar1_binary, hgf_binary_mab, hgf_whichworld, and
+  hgf_whatworld
+- Made infStates more consistent across models
+- Removed deprecated hgf_binary3l
+- Made fitModel explicitly return negative log-joint probability and negative
+  log-likelihood
+- Modified simModel to read configuration files of perceptual and observation
+  models
+- Abolished theta in hgf, hgf_binary, hgf_ar1, hgf_ar1_mab, hgf_ar1_binary,
+  hgf_binary_mab, and hgf_jget
+- Moved kappa estimation from logit-space to log-space for hgf, hgf_binary,
+  hgf_ar1, hgf_ar1_mab, hgf_ar1_binary, hgf_binary_mab, and hgf_jget
+- Introduced checking for implausible jumps in trajectories for hgf,
+  hgf_binary, hgf_ar1, hgf_ar1_mab, hgf_ar1_binary, hgf_binary_mab, and
+  hgf_jget
+- Adapted fitModel to deal with cases the <prc_model>_transp() function
+  performs operations important to the <model>() function
+- Introduced multinomial softmax decision model
+- Improved documentation for hgf_ar1_mab model
+- Added error IDs for all errors
+
+### v3.0
+- Improved error handling in tapas_fitModel()
+- Prefixed all function names with “tapas_”
+- Added rs_precision
+- Added rs_belief
+- Added rs_surprise
+- Added sutton_k1
+- Added hgf_ar1_mab
+- Added softmax for continuous responses
+- Improved checking of trajectory validity in HGF models
+- Debugged input handling in softmax_binary
+
+### v2.1
+- Introduced Bayesian parameter averaging
+- Amended calculation of log-priors in fitModel.m
+- Debugged construction of time axis in hgf_plotTraj
+- Debugged removal of placeholder field in estimate structure
+
+### v2.0
+- Estimation of Bayes optimal parameters added
+- infStates the same 3-dim array in hgf_binary as in hgf
+- Changes to softmax_binary: trial-by-trial rewards read from input matrix
+- hgf_binary generalized to n levels
+- Old hgf_binary lives on as hgf_binary3l
+- Input at irregular intervals enabled in hgf and hgf_binary
+- Support for constant drift in hgf and hgf_binary
+- Introduced use of placeholders in config files
+- quasinewton_optim: increased default maximum number of regularizations to 16
+- Automatic detection of upper bound on theta for hgf
+- Improved input checks
+- Support for AR(1) processes in new hgf_ar1
+- quasinewton_optim: improved resetting after exhaustion of regularizations
+
+### v1.0
+- Original release