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Uranie / Sampler
v4.11.0
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TMCMCSampling.h
Go to the documentation of this file.
TNormale * q
Variable representing a normal law which is used in all intermediary calculations.
Definition: TMCMCSampling.h:83
Definition: TNormale.h:47
TNtupleD * randomWalkMetropolisSampling(TNormale *f, TVectorD X)
Method of simulation of a gaussian vector using the algorithm random walk of MH. The components are...
Definition: TMCMCSampling.cxx:119
TMCMCSampling()
TNtupleD * gibbsSampling(TNormale *f, TVectorD X)
Method implementing the algorithm of Gibbs, used to simulate a gaussian vector.
Definition: TMCMCSampling.cxx:164
TNtupleD * varTimeMetropolisSampling(TNormale *f, TVectorD X)
Method of simulation of a gaussian vector using the algorithm variable-at-a-time of MH...
Definition: TMCMCSampling.cxx:62
Creation of the abstract class TSampler.
TNtupleD * NKCSampling(TMelange *mel, TVectorD *X)
Method allowing to deal with the "Normal Kernel Coupler", a MMC methode MCMC efficient for the simula...
Definition: TMCMCSampling.cxx:707
void Draw(TMelange *mel, TNtupleD *ntd, Option_t *option)
Method allowing to visualize the results of the MCMC methods programmed in this class, when the law has to be simulated is 2D dimension. Four visualizations are provided, allowing to follow the evolution of the simulation versus time, to get to know whether the values generated are distributed according to an expected law and after a certain number of iterations.
Definition: TMCMCSampling.cxx:473
TNtupleD * NKCSampling2(TMelange *mel, TVectorD *X)
Method implementing the NKC using 100 state vectors.
Definition: TMCMCSampling.cxx:811
Definition: TMelange.h:41
Definition: TMCMCSampling.h:75
void Draw1(TMelange *mel, TNtupleD *ntd, Option_t *option)
Definition: TMCMCSampling.cxx:445
Creation of the abstract class TDistribution.
Int_t selectComponentState()
Method used in the NKC, to determine the vector which will be used as mean of the instrumental law...
Definition: TMCMCSampling.cxx:685
