Given a markovchain object and reward values for every state, function calculates expected reward value after n steps.
expectedRewards(markovchain,n,rewards)
markovchain | the markovchain-class object |
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n | no of steps of the process |
rewards | vector depicting rewards coressponding to states |
returns a vector of expected rewards for different initial states
the function uses a dynamic programming approach to solve a recursive equation described in reference.
Stochastic Processes: Theory for Applications, Robert G. Gallager, Cambridge University Press
Vandit Jain
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