Marmote Core
The project aims at realizing the prototype of a software environment dedicated to modeling with Markov chains.
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▼CalgorithmicSampler | Abstraction for algorithms that produce samples of some unspecified distribution |
CpsiSampler | Abstraction for algorithms that produce samples of some unspecified distribution |
CAlias | Aliasing data |
CCost | Simulation data for CFTP algorithm |
▼CDistribution | A class for representing probability distributions |
▼CdiscreteDistribution | The general discrete distribution with finite support |
CbernoulliDistribution | The Bernoulli distribution with two values |
CdiracDistribution | The Dirac distribution concentrated at some point |
CuniformDiscreteDistribution | The uniform discrete distribution |
CexponentialDistribution | The class representing the (negative) exponential distribution |
CgeometricDistribution | The geometric distribution with starting value 0. The parameter "p" is called "ratio". The Geometric distribution is discrete but does not inherit from discreteDistribution because its range is infinite |
CpoissonDistribution | The Poisson distribution. The parameter is called "lambda". The Poisson distribution is discrete but does not inherit from discreteDistribution because its range is infinite |
CtemplateDistribution | The general template distribution to be instantiated |
CuniformDistribution | The continuous uniform distribution over some interval |
Celement | |
Cextension | |
CHBF | Storage of matrix in Harwell Boeing Format |
Citem | |
CLAW_DESC | |
CLAW_LIST | |
▼CmarkovChain | Markov Chain class |
Cfelsenstein81 | Ajout de fonctionalites sur les matrices F81 (Felsenstein 81) Ce sont des matrices 4x4 qui sont caracterisees par: un vecteur de 4 probabilites p[0], p[1], p[2], p[3] un parametre de vitesse mu > 0 |
Chomogeneous1DBirthDeath | The 1-dimensional birth and death process with homogeneous transition rates. This model is characterized by: |
Chomogeneous1DRandomWalk | The 1-dimensional random walk with homogeneous transition probabilities. This model is characterized by: |
ChomogeneousMultiDRandomWalk | The general d-dimensional random walk with homogeneous transition probabilities. This model is characterized by: |
▼CmarmoteSet | The mother class representing abstract sets |
CmarmoteBox | |
CmarmoteInterval | The class describing a finite integer interval |
CsimulationResult | The class for transmitting (Monte Carlo) simulation results between objects. Simulation results may be diverse: this structure should be able to accomodate each of the results, even if they are not all present at the same time. Results include: trajectories, empirical frequencies |
▼CtransitionStructure | Abstract class for transition structures. These are structures which describe transitions to one state to another one, to which is attached a numeric label. Typical instances should be one-step transition matrices of discrete-time Markov chains, and infinitesimal generators of continuous-time Markov chains. It is also possible that the origin state space and the destination state space are different |
CeventMixture | |
CmultiDimHomTransition | Class for multidimensional, homogeneous random walk transition structures. These are characterized by |
CsparseMatrix | Class sparseMatrix: implementation of a transition structure using the sparse matrix data structure. Elements of the transition structure (matrix) are stored by row, using two arrays containing indices of columns, and values of entries. A priori, only non-zero entries are stored but this is not a requirement |