RECS toolbox
============
[![DOI](https://zenodo.org/badge/1478253.svg)](https://zenodo.org/badge/latestdoi/1478253)
A MATLAB solver for nonlinear, dynamic, stochastic, rational expectations
equilibrium models. RECS stands for "Rational Expectations Complementarity
Solver". This name emphasizes that RECS has been developed specifically to solve
models that include complementarity equations, also known as models with
occasionally binding constraints.
[Christophe Gouel](http://www.christophegouel.com) (<christophe.gouel@inra.fr>)
**Main page is at**: [www.recs-solver.org](http://www.recs-solver.org).
## Download
RECS Toolbox releases are available at
<https://github.com/christophe-gouel/RECS/releases>.
Why is this archive 20 MB? Much of this size is due to an executable for
Windows. The executable file includes a complete Python distribution necessary
to parse RECS model files.
## Dependencies
* MATLAB R2011b or later.
* [CompEcon toolbox](http://www4.ncsu.edu/~pfackler/compecon/). RECS depends on
the CompEcon toolbox for many programs (especially with respect to
interpolation). Please follow CompEcon installation instructions and do not
forget to create the mex files if you want your models solved in a reasonable
time.
### Optional dependencies
* [Path solver for MATLAB](http://pages.cs.wisc.edu/~ferris/path.html). Path is
the reference solver for mixed complementarity problems. Its installation is
highly recommended if difficult complementarity problems need to be solved.
* MATLAB Optimization Toolbox. The solver fsolve can be used to solve both the
equilibrium equations and the rational expectations equilibrium.
* MATLAB Parallel Computing Toolbox. This toolbox allows many RECS programs to
be run in parallel to speed-up computation.
## Installation instructions
1. [Download the latest RECS archive](https://github.com/christophe-gouel/RECS/releases) and unzip
it into a folder, called here `recsfolder` (avoid folder names that include
spaces, even for parent folders).
2. Install the CompEcon toolbox:
1. [Download the CompEcon toolbox archive](http://www4.ncsu.edu/~pfackler/compecon/);
2. Unzip the archive into a folder, called here `compeconfolder`;
3. Add CompEcon to the MATLAB path: `addpath('compeconfolder/CEtools','compeconfolder/CEdemos')`;
4. Type `mexall` in MATLAB prompt to create all CompEcon mex files.
3. (optional) Install other dependencies.
4. Add the RECS folder to the MATLAB path: `addpath('recsfolder')`.
5. On Windows, you are all set. On other architectures, you will have to install
some Python packages. see instructions below.
6. You can test your installation by running RECS demonstration files by typing
`recsdemos`. You can also access RECS documentation in MATLAB by typing `doc`.
### Install Python dependencies
Python 2.7.X and the following packages are required on Linux and Mac, and on
Windows when installing from source:
* [Python 2.7.X](http://www.python.org/download/). Python is preinstalled on
Linux and Mac, but you should check the version number.
* [NumPy](http://www.numpy.org/).
* [PyYaml](http://pyyaml.org/wiki/PyYAML).
* [SymPy](http://sympy.org), version 0.7.2.
To make the Python programs available to RECS, you have two options:
* Install them in a virtual Python environment. By default, RECS looks for a
folder PythonVirtualEnv inside the Python folder. To do the installation,
from RECS folder type in a terminal
cd Python
virtualenv PythonVirtualEnv
source PythonVirtualEnv/bin/activate
pip install numpy PyYAML sympy==0.7.2
deactivate
If your default Python installation is not the version 2.7.X, replace the
second command by
virtualenv PythonVirtualEnv -p /usr/bin/python2.7
where `/usr/bin/python2.7` should be replaced by the address of your Python
2.7.X interpreter.
Alternatively, if your Python distribution is Anaconda, you can create from
RECS folder the virtual environment by
conda create -p ./Python/PythonVirtualEnv python=2.7 numpy PyYAML sympy==0.7.2
* Install them in your default Python installation (recommended only if you do
not use Python otherwise). In this case, just type
pip install numpy PyYAML sympy==0.7.2
## Installation from source
If you want to work with the bleeding edge version of RECS, which may be
unstable, or if you want to contribute to RECS development, you need to install
RECS from source. The installation requires [Git](http://git-scm.com/).
When installing from source, all platforms (Linux, Mac, and Windows) require
[Python 2.7.X](http://www.python.org/download/), along with
[NumPy](http://www.numpy.org/), [PyYaml](http://pyyaml.org/wiki/PyYAML), and
[SymPy](http://sympy.org) version 0.7.2. See above for instructions.
Optionnaly, under Windows, to be able to generate a binary to run to the solver
without a Python installation, one can also install
[PyInstaller](http://www.pyinstaller.org/) and make its folder available in
Windows Path.
1. Download the latest version of RECS from the git repository by typing in a
command line: `git clone https://github.com/christophe-gouel/RECS.git recs`
2. From RECS folder (`cd recs`), download recs submodules with two commands:
`git submodule init` and `git submodule update`.
3. Install the CompEcon toolbox:
1. [Download the CompEcon toolbox archive](http://www4.ncsu.edu/~pfackler/compecon/);
2. Unzip the archive into a folder, called here `compeconfolder`;
3. Add CompEcon to the MATLAB path: `addpath('compeconfolder/CEtools','compeconfolder/CEdemos')`;
4. Type `mexall` in MATLAB prompt to create all CompEcon mex files.
4. (optional) Install other dependencies.
5. Add the RECS folder to the MATLAB path: `addpath('recsfolder')`.
6. Finalizes RECS installation from source by running in MATLAB the function
`recsInstall`.
7. You can test your installation by running RECS demonstration files by typing
`recsdemos`. You can also access RECS documentation in MATLAB by typing `doc`.
## Source
RECS source can be found on the following git repository:
<https://github.com/christophe-gouel/RECS.git>.
## License
Unless stated otherwise, all files in the RECS toolbox are licensed using the
Expat license, a permissive free software license. Please see the [software
license](https://raw.github.com/christophe-gouel/RECS/master/LICENSE.txt) for
more information.
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RECS:非线性,动态,随机,有理期望均衡模型的求解器
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yaml:15个
xml:2个
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RECS:非线性,动态,随机,有理期望均衡模型的求解器 (127个子文件)
Archive.bat 1KB
layoutfunctionhelp.css 3KB
bullet-recs.gif 58B
.gitattributes 11B
.gitignore 218B
.gitmodules 96B
nsoli.m 22KB
lmmcp.m 18KB
recsSimul.m 13KB
recsSimulSP.m 11KB
recsmodel.m 11KB
recsSolveREE.m 11KB
def_sre.m 8KB
ug_options.m 8KB
MCP.m 8KB
recsSolveDeterministicPbSP.m 7KB
Publish_recs_help.m 7KB
recsSSSP.m 7KB
mcpsolve.m 7KB
simulate.m 7KB
recsmodelsp.m 6KB
recsDeterministicPbSP.m 6KB
recsEquilibrium.m 6KB
recspathmcp.m 6KB
recsSolveREEIter.m 6KB
blktridiag.m 6KB
recsSS.m 6KB
installation.m 6KB
first_guess.m 5KB
recsFirstGuess.m 5KB
recsCheck.m 5KB
recsmodelsp2model.m 5KB
ug_model_files.m 5KB
recsSolveREESP.m 5KB
catstruct.m 5KB
recsSolveDeterministicPb.m 5KB
runeqsolver.m 5KB
recsAuxiliarySP.m 5KB
recsSolveREEFull.m 5KB
recsAuxiliary.m 4KB
SA.m 4KB
recsFirstGuessSP.m 4KB
gro3.m 4KB
recsSolveEquilibrium.m 4KB
recsAccuracy.m 4KB
testsjacobians.m 4KB
sto4.m 4KB
parallel.m 4KB
recsAccuracySP.m 4KB
recsDeterministicPb.m 4KB
recsConvert.m 3KB
recsIRF.m 3KB
recsDecisionRules.m 3KB
benchmark.m 3KB
numjac.m 3KB
ug_model_struct.m 3KB
recs_functions.m 3KB
mcptransform.m 3KB
sto6SP.m 3KB
gro2.m 3KB
recsSolveLocal.m 3KB
recsSolveREEFiniteHorizon.m 3KB
solution_methods.m 3KB
solve_REE.m 3KB
recs_product_page.m 3KB
numhessian.m 3KB
Contents.m 2KB
gro1.m 2KB
sto1.m 2KB
ug_interpolation.m 2KB
sto5.m 2KB
sto2.m 2KB
recsInstall.m 2KB
cs1.m 2KB
sto3.m 2KB
recsinterpinit.m 2KB
ug_solvers_eq.m 2KB
SCP.m 2KB
spblkdiag.m 2KB
recsResidual.m 2KB
Diagnostics.m 2KB
sto2simu.m 2KB
ss.m 2KB
recsdemos.m 2KB
sto6.m 1KB
demos.m 1KB
Contents.m 1KB
recsAdaptativeAccuracy.m 1004B
cs2.m 894B
pathtransform.m 870B
arraymult.m 500B
sto1FX.m 488B
autocor.m 482B
ncpsolvetransform.m 443B
user_guide.m 410B
filetohelp.m 388B
gro3problem.m 377B
isfilepresent.m 339B
getting_started.m 272B
ug_setting_up.m 222B
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