Description Usage Arguments Value Examples
View source: R/stochastic_growth_model.R
The function Markovmoments
computes the expectation, variance, autocovariance and autocorrelation of a Markov process.
1 | Markovmoments(states, ptm, ...)
|
states |
A numerical vector with the states of the Markov process. |
ptm |
The probability transition matrix, a square matrix of dimension length(states) whose columns sum to one. |
... |
Additional arguments. |
It returns a list containing:
Expectation |
The mean of the process. |
Variance |
The variance of the process. |
Autocovariance |
The autocovariance of the process. |
Autocorrelation |
The autocorrelation of the process. |
Stationary distribution |
The stationary distribution of the process, used for the computation of the moments. |
1 2 3 4 | a <- c(-1, 1)
A <- matrix(c(0.5, 0.6,
0.5, 0.4), 2, 2)
Markovmoments(a, A)
|
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