enorm eEF libEF.h class sq_T sq_T vec vec enorm< sq_T >::mu mu mean value enorm< fsqmat >::_mu enorm< sq_T >::evalpdflog enorm< fsqmat >::mean enorm< sq_T >::sample enorm< fsqmat >::set_mu enorm< sq_T >::set_parameters sq_T sq_T enorm< sq_T >::R R Covariance matrix in decomposed form. enorm< fsqmat >::_R enorm< sq_T >::evalpdflog enorm< fsqmat >::getR enorm< sq_T >::lognc enorm< sq_T >::sample enorm< sq_T >::set_parameters int int enorm< sq_T >::dim dim dimension (redundant from rv.count() for easier coding ) enorm< sq_T >::sample RV RV epdf::rv rv Identified of the random variable. epdf::_rv egamma::evalpdflog egiw::evalpdflog egamma::lognc eEmp::mean emix::mean euni::sample egamma::sample epdf::sampleN emix::set_parameters enorm< sq_T >::enorm (RV &rv) enorm RV & rv Default constructor. void void enorm< sq_T >::set_parameters (const vec &mu, const sq_T &R) set_parameters const vec & mu const sq_T & R Set mean value mu and covariance R. enorm< sq_T >::mu enorm< sq_T >::R KalmanCh::set_est void void enorm< sq_T >::tupdate (double phi, mat &vbar, double nubar) tupdate tupdate double phi mat & vbar double nubar tupdate in exponential form (not really handy) void void enorm< sq_T >::dupdate (mat &v, double nu=1.0) dupdate dupdate mat & v double nu 1.0 dupdate in exponential form (not really handy) vec vec enorm< sq_T >::sample () const sample sample Returns the required moment of the epdf. Returns a sample, $x$ from density $epdf(rv)$ enorm< sq_T >::dim enorm< sq_T >::mu enorm< sq_T >::R mat mat enorm< sq_T >::sample (int N) const sample int N TODO is it used? enorm< sq_T >::dim enorm< sq_T >::mu enorm< sq_T >::R double double enorm< sq_T >::eval (const vec &val) const eval eval const vec & val Compute probability of argument val. enorm< sq_T >::evalpdflog double double enorm< sq_T >::evalpdflog (const vec &val) const evalpdflog evalpdflog const vec & val Compute log-probability of argument val. enorm< sq_T >::lognc enorm< sq_T >::mu enorm< sq_T >::R EKF< sq_T >::bayes EKFCh::bayes KalmanCh::bayes enorm< sq_T >::eval double double enorm< sq_T >::lognc () const lognc lognc logarithm of the normalizing constant, $\mathcal{I}$ enorm< sq_T >::R enorm< sq_T >::evalpdflog vec vec enorm< sq_T >::mean () const mean mean return expected value vec & vec& enorm< sq_T >::_mu () _mu returns a pointer to the internal mean value. Use with Care! void void enorm< sq_T >::set_mu (const vec mu0) set_mu const vec mu0 access function EKFfixed::bayes EKFfull::bayes sq_T & sq_T& enorm< sq_T >::_R () _R returns pointers to the internal variance and its inverse. Use with Care! mat mat enorm< sq_T >::getR () getR access method mat mat epdf::sampleN (int N) const sampleN int N Returns N samples from density $epdf(rv)$. RV::count epdf::rv RV & RV& epdf::_rv () _rv access function, possibly dangerous! epdf::rv emix::set_parameters Gaussian density with positive definite (decomposed) covariance matrix. More?... enorm< sq_T > epdf enorm< fsqmat > < fsqmat > enorm< chmat > < chmat > enorm< ldmat > < ldmat > eEF enorm< sq_T > R sq_T epdf rv RV eEF enorm_mu enorm_R enorm_rv enormdim enormdupdate enormeEF enormenorm enormepdf enormepdf enormeval enormevalpdflog enormgetR enormlognc enormmean enormmu enormR enormrv enormsample enormsample enormsampleN enormset_mu enormset_parameters enormtupdate enorm~epdf