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https://github.com/markjolah/priorhessian
Library for fast computation of log-likelihoods and derivatives of multivariate prior distributions
https://github.com/markjolah/priorhessian
log-likelihood prior
Last synced: 23 days ago
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Library for fast computation of log-likelihoods and derivatives of multivariate prior distributions
- Host: GitHub
- URL: https://github.com/markjolah/priorhessian
- Owner: markjolah
- License: apache-2.0
- Created: 2017-10-23T19:40:40.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-07-01T02:01:13.000Z (over 5 years ago)
- Last Synced: 2024-03-19T18:26:17.917Z (10 months ago)
- Topics: log-likelihood, prior
- Language: C++
- Homepage: https://markjolah.github.io/PriorHessian
- Size: 17.4 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Prior Hessian
Library for fast computation of log-likelihoods and derivatives of multivariate priors defined as composites of univariate multivariate distributions especially designed for support of
Archimedean copulas.
## Documentation
The PriorHessian Doxygen documentation can be build with the `OPT_DOC` CMake option and is also available on online:
* [PriorHessian HTML Manual](https://markjolah.github.io/PriorHessian/index.html)
* [PriorHessian PDF Manual](https://markjolah.github.io/PriorHessian/pdf/PriorHessian-0.2.1-reference.pdf)
* [PriorHessian github repository](https://github.com/markjolah/PriorHessian)
## Installation
The PriorHessian library uses CMake and is designed to be installed either as a native package, or as a relocatable package in an arbitrary install prefix. The default build script will install to the `_install` directory underneath the repository root.
* **Default release build script**
* builds to `${BUILD_PATH}` if set or default of: `${CMAKE_SOURCE_DIR}\_build\Release`
* installs to `${INSTALL_PATH}` if set or default of: `${CMAKE_SOURCE_DIR}\_install`
```
$ ./build.sh
```
* **Default Debug build script**
* builds to `${BUILD_PATH}` if set or default of: `${CMAKE_SOURCE_DIR}\_build\Debug`
* installs to `${INSTALL_PATH}` if set or default of: `${CMAKE_SOURCE_DIR}\_install`
```
$ ./build.debug.sh
```
* **Manual CMake Build**
```
$ cmake -H. -B -DCMAKE_INSTALL_PREFEX= -DCMAKE_BUILD_TYPE=Release
$ cd && make -j install
```
### Dependencies
* [*Armadillo*](http://arma.sourceforge.net/docs.html) - A high-performance array library for C++.
* *BLAS* - A BLAS implemenation: [Netlib BLAS reference](http://www.netlib.org/blas/) or [*OpenBlas*](https://www.openblas.net/)
* *LAPACK* - A Lapack implemenation: [Netlib LAPACK reference](http://www.netlib.org/lapack/)
Note the `OPT_BLAS_INT64` CMake option controls whether Armadillo uses BLAS and LAPACK libraries that use 64-bit interger indexing.
Matlab uses 64-bit by default, and to link PriorHessian to Matlab MEX libraries, this option must be on. Many linux systems only provide 32-bit integer versions of BLAS and Lapack, and the option can be disabled if Matlab support is not a concern and 64-bit support is difficult to manage on
### CMake Options
#### Standard options
* `BUILD_SHARED_LIBS` - Build shared libraries [Default: On]
* `BUILD_STATIC_LIBS` - Build static libraries [Default: On]
* `BUILD_TESTING` - Build tests [Default: On if `CMAKE_BUILD_TYPE=Debug`]
* `OPT_INSTALL_TESTING` - Install tests. [Default: Off]
* `OPT_DOC` - Build and install documentation (enables `make doc` and `make pdf`) [Default: Off]
* `OPT_EXPORT_BUILD_TREE` - Enable CMake export and `find_package(BacktraceException)` support from the build-tree.
#### Dependency options
* `OPT_BLAS_INT64` - Enable 64-bit integer BLAS library support [Default: Off]
### External Projects
These packages are specialized CMake projects. If they are not currently installed on the development machines we use the [AddExternalDependency.cmake](https://github.com/markjolah/UncommonCMakeModules/blob/master/AddExternalDependency.cmake) which will automatically download, configure, build and install to the `CMAKE_INSTALL_PREFIX`, enabling their use through the normal CMake `find_package()` system.
* [BacktraceException](https://github.com/markjolah/BacktraceException) - For exception backtraces when debugging (especially in Matlab).
## Motivation
For many likelihood-based methods, they can be extended to Bayesian methods like MAP Estimation and MCMC Posterior sampling,
by incorporating a prior. This prior must provide fast methods for computing log-likelihood and it's derivatives over the
parameter space. The prior log-likelihood, as well as it's gradient and hessian are then added to the equivalent quantities from the likelihood to create a Bayesian objective for MAP Estimation.
## Static Polymorphism
The PriorHessian library is designed using static polymorphism (templates), and as such avoids virtual functions for small-grained tasks, and instead uses templates, which allow many small functions to be inlined. This aggressive inlining by the compiler produces log-likelihood, gradient, and hessian functions that are nearly as fast as hand-coded functions. But our flexible [`CompositeDist`]() class is able to be easily created with any mix of [`UnivariateDist`]() and [`MultivariateDist`]() elements.
In [Mappel](https://github.com/markjolah/Mappel) we use this ability to create heterogeneous priors for each Model's parameters, (e.g., [x,y,I,bg,sigma]).
Functionally, the PriorHessian library stores sequences of distributions as `std::tuples`. Using this approach as opposed to
the runtime polymorphism of using `std::vector>` gains several advantages.
Most importantly, without the need for virtual functions, the tuple-based approach has the ability to inline the many
small computational functions that must be combined for every call to compute the log-likelihood or other computationally important quantities.