BayesOpt
File List
Here is a list of all documented files with brief descriptions:
 ackley.m
 bayesopt.hBayesOpt wrapper for C interface
 bayesopt.hppBayesOpt main C++ interface
 bayesoptbase.cpp
 bayesoptbase.hppBayesOpt common module for interfaces
 bayesoptcatmex.c
 bayesoptcont.cpp
 bayesoptcont.m
 bayesoptdisc.cpp
 bayesoptdisc.m
 bayesoptdiscmex.c
 bayesoptextras.hHelper functions to Matlab/Octave wrappers
 bayesoptmex.c
 bayesoptmodule.pyBayesOpt wrapper for Python interface (OOP)
 bayesoptwpr.cpp
 bo_branin.cpp
 bo_branin_display.cpp
 bo_branin_mcmc.cpp
 bo_branin_timed.cpp
 bo_camelback.cpp
 bo_compare.cpp
 bo_cont.cpp
 bo_disc.cpp
 bo_display.cpp
 bo_hartmann.cpp
 bo_oned.cpp
 bopt_state.cpp
 bopt_state.hppRepresentation of a optimization state
 boundingbox.hppModule for box constrain management
 branin.m
 branin_system_calls.cpp
 branin_xml.cpp
 braninhighdim.m
 camelback.m
 2.8.11.2/CompilerIdC/CMakeCCompilerId.c
 2.8.12.2/CompilerIdC/CMakeCCompilerId.c
 CompilerIdC/CMakeCCompilerId.c
 2.8.11.2/CompilerIdCXX/CMakeCXXCompilerId.cpp
 2.8.12.2/CompilerIdCXX/CMakeCXXCompilerId.cpp
 CompilerIdCXX/CMakeCXXCompilerId.cpp
 compile_matlab.m
 compile_octave.m
 conditionalbayesprocess.cpp
 conditionalbayesprocess.hppKernel based nonparametric process, conditional on kernel hyperparameters
 config.h
 criteria_a_opt.hppA-optimality (uncertainty) based criteria
 criteria_combined.hppAbstract module for combined criteria
 criteria_distance.hppCost for selecting distant points
 criteria_ei.hppExpected improvement based criteria
 criteria_expected.hppCriterion based on the expected value of the function
 criteria_functors.cpp
 criteria_functors.hppAbstract and factory modules for criteria
 criteria_hedge.cpp
 criteria_hedge.hppPortfolio selection of criteria based on Hedge algorithm
 criteria_lcb.hppLower confidence bound based criteria
 criteria_mi.hpp
 criteria_poi.hppProbability of improvement
 criteria_prod.hppProduct of multiple criteria
 criteria_sum.hppSum of multiple criteria
 criteria_thompson.hppThompson and optimistic sampling criteria
 dataset.cpp
 dataset.hppDataset model
 demo_cam.py
 demo_dimscaling.py
 demo_distance.py
 demo_multiprocess.py
 demo_quad.py
 demo_rembo.m
 demo_test.m
 displaygp.cpp
 displaygp.hppPlots the evolution (nonparametric process, criteria or contour plots) of 1D and 2D problems
 dll_stuff.h
 eval_branin.py
 eval_branin_xml.py
 filedb.cpp
 filedb.hppA simple file-based database model
 fileparser.cpp
 fileparser.hppFunctions to write and parse data files
 foo.m
 gauss_distribution.cpp
 gauss_distribution.hppGaussian probability distribution
 gaussian_process.cpp
 gaussian_process.hppStandard zero mean gaussian process with noisy observations
 gaussian_process_hierarchical.cpp
 gaussian_process_hierarchical.hppHierarchical model for Gaussian process
 gaussian_process_ml.cpp
 gaussian_process_ml.hppGaussian process with ML parameters
 gaussian_process_normal.cpp
 gaussian_process_normal.hppGaussian process with normal prior on the parameters
 gpmlnlopt.m
 gpmltest.m
 gridsampling.hppRegular grid sampling
 hartmann.m
 indexvector.hppGenerators for index vectors
 inneroptimization.cpp
 inneroptimization.hppC++ wrapper of the NLOPT library
 kernel_atomic.hppAtomic (simple) kernel functions
 kernel_combined.hppKernel functions that combine other kernels
 kernel_const.hpp
 kernel_functors.cpp
 kernel_functors.hppKernel (covariance) functions
 kernel_gaussian.hpp
 kernel_hamming.hpp
 kernel_linear.hpp
 kernel_matern.hpp
 kernel_polynomial.hpp
 kernel_prod.hpp
 kernel_rq.hpp
 kernel_sum.hpp
 kernelregressor.cpp
 kernelregressor.hppNonparametric process abstract module
 langermann.m
 lhs.hppLatin Hypercube Sampling
 log.hppModules and helper macros for logging
 mcmc_sampler.cpp
 mcmc_sampler.hppMarkov Chain Monte Carlo algorithms
 mean_atomic.hppAtomic (simple) parametric functions
 mean_combined.hppParametric functions that combine other functions
 mean_functors.cpp
 mean_functors.hppMean (parametric) functions
 michalewicz.m
 nei.m
 neinlopt.m
 nonparametricprocess.cpp
 nonparametricprocess.hppAbstract module for a Bayesian regressor
 optimizable.hppAbstract class for optimizable objects
 param_loader.cpp
 param_loader.hppAllows to load parameters from file
 parameters.cpp
 parameters.hParameter definitions
 parameters.hppParameter definitions
 parser.cpp
 parser.hppFunctions to parse strings
 posterior_empirical.cpp
 posterior_empirical.hpp
 posterior_fixed.cpp
 posterior_fixed.hppPosterior model based on fixed kernel parameters
 posterior_mcmc.cpp
 posterior_mcmc.hppPosterior distribution on GPs based on MCMC over kernel parameters
 posteriormodel.cpp
 posteriormodel.hppAbstract interface for posterior model/criteria
 prob_distribution.hppInterface for probability models
 quadratic.m
 randgen.hppBoost types for random number generation
 readlog.m
 rosenbrock.m
 specialtypes.hppBoost vector and matrix types
 student_t_distribution.cpp
 student_t_distribution.hppStudent's t probability distribution
 student_t_process_jef.cpp
 student_t_process_jef.hppStudent T process with Jeffreys priors
 student_t_process_nig.cpp
 student_t_process_nig.hppStudent's t process with Normal-Inverse-Gamma hyperprior on mean and signal variance parameters
 testfunctions.hpp
 testmatlab.c
 ublas_cholesky.hppCholesky decomposition
 ublas_elementwise.hppElementwise operations for ublas vector/matrix
 ublas_extra.cpp
 ublas_extra.hppExtra functions for Ublas library
 ublas_trace.hpp
 UINT32_T.c