Fit a function to data using Bayesian methods. More...
#include <fit_bayes.h>
This class is experimental.
This class uses Markov Chain Monte Carlo (MCMC) and marginal estimation to give a probability distribution for parameters in a fit.
Also make weight_fun() an object of type multi_func_t?
Offer two ways to do the evidence: direct MC or the interpolation method from SLB13
Build upon gen_fit_funct instead of fit_funct?
Definition at line 77 of file fit_bayes.h.
Public Types | |
typedef boost::numeric::ublas::vector< double > | ubvector |
typedef boost::numeric::ublas::matrix< double > | ubmatrix |
typedef boost::numeric::ublas::vector< int > | ubvector_int |
Public Member Functions | |
virtual void | evidence (size_t ndat, vec_t &xdat, vec_t &ydat, vec_t &yerr, size_t npar, vec_t &plo2, vec_t &phi2, multi_func_t &prior_fun, double &evi, double &err) |
Compute the evidence. | |
virtual double | weight_fun (size_t ndat, const vec_t &xdat, const vec_t &ydat, const vec_t &yerr, size_t npar, const vec_t &par) |
The weight function (based on a ![]() | |
virtual int | fit (size_t ndat, vec_t &xdat, vec_t &ydat, vec_t &yerr, size_t npar, vec_t &plo2, vec_t &pmax, vec_t &phi2, vec_t &plo_err, vec_t &pmax_err, vec_t &phi_err, fit_func_t &fitfun, multi_func_t &prior_fun) |
Fit ndat data points in xdat and ydat with errors yerr to function fitfun with npar parameters. More... | |
virtual int | fit_hist (size_t ndat, vec_t &xdat, vec_t &ydat, vec_t &yerr, size_t npar, vec_t &plo2, vec_t &phi2, std::vector< hist > &par_hist, fit_func_t &fitfun, multi_func_t &prior_fun) |
Desc. More... | |
Public Attributes | |
size_t | n_warm_up |
Number of warmup iterations (default 100) | |
size_t | n_iter |
Number of total iterations (default 1000) | |
size_t | hsize |
Histogram size (default 20) | |
size_t | nmeas |
Number of measurements (default 20) | |
multi_func_t * | pri |
Prior distribution. | |
rng_gsl | gr |
Random number generator. | |
mcarlo_vegas | def_inte |
Default Monte Carlo integrator. | |
Protected Member Functions | |
virtual double | integrand (size_t npar, const vec_t &par) |
The integrand for the evidence. | |
Protected Attributes | |
fit_func_t * | ff |
User-specified function. | |
size_t | lndat |
Number of data points. | |
vec_t * | lxdat |
X-values. | |
vec_t * | lydat |
Y-values. | |
vec_t * | lyerr |
Y-errors. | |
|
inlinevirtual |
The initial values of the parameters should be specified in par
.
Definition at line 178 of file fit_bayes.h.
|
inlinevirtual |
For each measurement block, this function collects the data for all the parameters into 1d histogram objects. Then, at the end of the block, the histogram information is added to a hist object for each parameter.
Definition at line 335 of file fit_bayes.h.
Documentation generated with Doxygen. Provided under the
GNU Free Documentation License (see License Information).