scalation.simulation.state
Members list
Type members
Classlikes
The MarkovCT class supports the creation and use of Continuous-Time Markov Chains 'CTMC's. Note: the transition matrix 'tr' gives the state transition rates off-diagonal. The diagonal elements must equal minus the sum of the rest of their row. Transient solution: Solve the Chapman-Kolmogorov differential equations. Equilibrium solution (steady-state): solve for p in p * tr = 0.
The MarkovCT class supports the creation and use of Continuous-Time Markov Chains 'CTMC's. Note: the transition matrix 'tr' gives the state transition rates off-diagonal. The diagonal elements must equal minus the sum of the rest of their row. Transient solution: Solve the Chapman-Kolmogorov differential equations. Equilibrium solution (steady-state): solve for p in p * tr = 0.
Value parameters
- tr
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the transition rate matrix
Attributes
- See also
- Supertypes
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class Objecttrait Matchableclass Any
The MarkoveChain class supports the creation and use of Discrete-Time Markov Chains (DTMC)s. Transient solution: compute the next state p = π * a where π is the current state probability vector and a is the transition probability matrix. Equilibrium solution (steady-state): solve for π in π = π * a.
The MarkoveChain class supports the creation and use of Discrete-Time Markov Chains (DTMC)s. Transient solution: compute the next state p = π * a where π is the current state probability vector and a is the transition probability matrix. Equilibrium solution (steady-state): solve for π in π = π * a.
Value parameters
- a
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the transition probability matrix
Attributes
- Supertypes
-
class Objecttrait Matchableclass Any
Attributes
- Supertypes
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class Objecttrait Matchableclass Any
Attributes
- Supertypes
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class Objecttrait Matchableclass Any
Attributes
- Supertypes
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class Objecttrait Matchableclass Any
Attributes
- Supertypes
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class Objecttrait Matchableclass Any
Attributes
- Supertypes
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class Objecttrait Matchableclass Any
Attributes
- Supertypes
-
class Objecttrait Matchableclass Any
Value members
Concrete methods
The markovCTTest main function tests the MarkovCT class (Continuous-Time Markov Chains).
The markovCTTest main function tests the MarkovCT class (Continuous-Time Markov Chains).
runMain scalation.simulation.state.markovCTTest
Attributes
The markovChainTest main function tests the MarkovChain class (Discrete-Time Markov Chains).
The markovChainTest main function tests the MarkovChain class (Discrete-Time Markov Chains).
runMain scalation.simulation.state.markovChainTest
Attributes
The markovChainTest2 main function tests the MarkovChain class (Discrete-Time Markov Chains). Six-state coin game.
The markovChainTest2 main function tests the MarkovChain class (Discrete-Time Markov Chains). Six-state coin game.
runMain scalation.simulation.state.markovChainTest2
Attributes
The markovChainTest3 main function tests the MarkovChain class (Discrete-Time Markov Chains). Six-state coin game: Tail (-1), Head (+1).
The markovChainTest3 main function tests the MarkovChain class (Discrete-Time Markov Chains). Six-state coin game: Tail (-1), Head (+1).
runMain scalation.simulation.state.markovChainTest3
Attributes
The markovChainTest4 main function tests the MarkovChain class.
The markovChainTest4 main function tests the MarkovChain class.
Attributes
- See also
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Introduction to Probabulity Models, 3rd Ed., Ross, p. 146.
runMain scalation.simulation.state.markovChainTest4
The markovChainTest5 main function tests the MarkovChain class. A simple SEIR model: 40, 8, 10 days between S->E, E->I, I-R.
The markovChainTest5 main function tests the MarkovChain class. A simple SEIR model: 40, 8, 10 days between S->E, E->I, I-R.
runMain scalation.simulation.state.markovChainTest5