Marmote Core
The project aims at realizing the prototype of a software environment dedicated to modeling with Markov chains.
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Class Hierarchy
This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 123]
oCDistributionA class for representing probability distributions
|oCdiscreteDistributionThe general discrete distribution with finite support
||oCbernoulliDistributionThe Bernoulli distribution with two values
||oCdiracDistributionThe Dirac distribution concentrated at some point
||\CuniformDiscreteDistributionThe uniform discrete distribution
|oCexponentialDistributionThe class representing the (negative) exponential distribution
|oCgeometricDistributionThe geometric distribution with starting value 0. The parameter "p" is called "ratio"
|oCtemplateDistributionThe general template distribution to be instantiated
|\CuniformDistributionThe continuous uniform distribution over some interval
oCelement
oCextension
oCitem
oCLAW_DESC
oCLAW_LIST
oCmarkovChainMarkov Chain class
|oCfelsenstein81Ajout 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
|oChomogeneous1DBirthDeathThe 1-dimensional birth and death process with homogeneous transition rates. This model is characterized by:
|oChomogeneous1DRandomWalkThe 1-dimensional random walk with homogeneous transition probabilities. This model is characterized by:
|\ChomogeneousMultiDRandomWalkThe general d-dimensional random walk with homogeneous transition probabilities. This model is characterized by:
oCmarmoteSetThe mother class representing abstract sets
|oCmarmoteBox
|\CmarmoteIntervalThe class describing a finite integer interval
oCsimulationResultThe 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
\CtransitionStructureAbstract 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
 oCeventMixture
 oCmultiDimHomTransitionClass for multidimensional, homogeneous random walk transition structures. These are characterized by
 \CsparseMatrixClass 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