CalcEmpiricalStationary: Calculation of the Empirical Stationary Distribution from an...
In bvegetabile/ccber: Estimation of Behavioral Entropy Rate
Description
Usage
Arguments
Value
Examples
Description
Calculation of the Empirical Stationary Distribution from an observed Markov Chain (first-order)
Usage
1
CalcEmpiricalStationary(event_seq, state_space)
Arguments
event_seq
Observed sequence of events as a Markov chain
state_space
State space of the observed Markov chain
Value
Estimate of the stationary distribution
Examples
1
2
3
4
t_mat <- matrix(c(0.3, 0.7, 0.6, 0.4), 2,2, T)
sim_mc <- SimulateMarkovChain(t_mat, n_sims = 500)
true_sm <- CalcEigenStationary(t_mat)
est_sm <- CalcEmpiricalStationary(sim_mc, 1:2)
bvegetabile/ccber documentation built on May 10, 2019, 1:15 p.m.
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Description Usage Arguments Value Examples
Description
Calculation of the Empirical Stationary Distribution from an observed Markov Chain (first-order)
Usage
1 | CalcEmpiricalStationary(event_seq, state_space)
|
Arguments
event_seq |
Observed sequence of events as a Markov chain |
state_space |
State space of the observed Markov chain |
Value
Estimate of the stationary distribution
Examples
1 2 3 4 | t_mat <- matrix(c(0.3, 0.7, 0.6, 0.4), 2,2, T)
sim_mc <- SimulateMarkovChain(t_mat, n_sims = 500)
true_sm <- CalcEigenStationary(t_mat)
est_sm <- CalcEmpiricalStationary(sim_mc, 1:2)
|
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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