markov

Documentation

Index

• func CreateTransitionMatrix(weights [][]int) (simulation.TransitionMatrix, error)
• func GetMemberOfInitialState(r *rand.Rand, weights []int) int
• type TransitionMatrix
  • func (t TransitionMatrix) NextState(r *rand.Rand, i int) int

Functions

func CreateTransitionMatrix

func CreateTransitionMatrix(weights [][]int) (simulation.TransitionMatrix, error)

CreateTransitionMatrix creates a transition matrix from the provided weights. TODO: Provide example usage

func GetMemberOfInitialState

func GetMemberOfInitialState(r *rand.Rand, weights []int) int

GetMemberOfInitialState takes an initial array of weights, of size n. It returns a weighted random number in [0,n).

Types

type TransitionMatrix

type TransitionMatrix struct {
	// contains filtered or unexported fields
}

TransitionMatrix is _almost_ a left stochastic matrix. It is technically not one due to not normalizing the column values. In the future, if we want to find the steady state distribution, it will be quite easy to normalize these values to get a stochastic matrix. Floats aren't currently used as the default due to non-determinism across architectures

func (TransitionMatrix) NextState

func (t TransitionMatrix) NextState(r *rand.Rand, i int) int

NextState returns the next state randomly chosen using r, and the weightings provided in the transition matrix.