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class MarkovModel<Parameter, State> < ForwardModel

Markov model.

The joint distribution is:

Graphical model depicting MarkovModel.

A model inheriting from MarkovModel overrides the parameter, initial and transition member fibers to specify the individual components of the joint distribution.

Member Variables

Name Description
θ:Parameter Parameter.
x:Iterator<State> States.

Member Functions

Name Description
start Start.
step Step.

Member Fibers

Name Description
parameter Parameter model.
initial Initial model.
transition Transition model.

Member Function Details


function start() -> Real

Start. Simulates the parameter model.


function step() -> Real

Step. Simulates the initial state, or the transition to the next state.

Member Fiber Details


fiber initial(x:State, θ:Parameter) -> Event

Initial model.

  • x: The initial state, to be set.
  • θ: The parameters.


fiber parameter(θ:Parameter) -> Event

Parameter model.

  • θ: The parameters, to be set.


fiber transition(x:State, u:State, θ:Parameter) -> Event

Transition model.

  • x: The current state, to be set.
  • u: The previous state.
  • θ: The parameters.