Given a markovchain object and reward values for every state, function calculates expected reward value after n steps.

expectedRewards(markovchain,n,rewards)

Arguments

markovchain

the markovchain-class object

n

no of steps of the process

rewards

vector depicting rewards coressponding to states

Value

returns a vector of expected rewards for different initial states

Details

the function uses a dynamic programming approach to solve a recursive equation described in reference.

References

Stochastic Processes: Theory for Applications, Robert G. Gallager, Cambridge University Press

Author

Vandit Jain

Examples

transMatr<-matrix(c(0.99,0.01,0.01,0.99),nrow=2,byrow=TRUE) simpleMc<-new("markovchain", states=c("a","b"), transitionMatrix=transMatr) expectedRewards(simpleMc,1,c(0,1))
#> [1] 0.01 1.99