Nothing
Code
summary(PH(subint_mat = matrix(c(-1.5, 0, 0, 1.5, -1, 0, 0, 1, -0.5), ncol = 3),
init_probs = c(1, 0, 0)))
Output
Subintensity matrix:
[,1] [,2] [,3]
[1,] -1.5 1.5 0.0
[2,] 0.0 -1.0 1.0
[3,] 0.0 0.0 -0.5
Initial probabilities:
[,1] [,2] [,3]
[1,] 1 0 0
Defect:
[1] 0
Mean: 3.666667
Variance: 5.444444
Code
summary(DPH(subint_mat = matrix(c(0.4, 0.24, 0.12, 0, 0.4, 0.2, 0, 0, 0.5),
ncol = 3, byrow = TRUE), init_probs = c(1, 0, 0)))
Output
Subintensity matrix:
[,1] [,2] [,3]
[1,] 0.4 0.24 0.12
[2,] 0.0 0.40 0.20
[3,] 0.0 0.00 0.50
Initial probabilities:
[,1] [,2] [,3]
[1,] 1 0 0
Defect:
[1] 0
Mean: 3
Variance: 3.777778
Code
summary(MPH(subint_mat = matrix(c(-3, 2, 0, 0, -2, 1, 0, 0, -1), nrow = 3,
byrow = TRUE), reward_mat = matrix(c(4.4, 2, 8.8, 4.3, 1.8, 2.3), nrow = 3,
ncol = 2), init_probs = c(1, 0, 0)))
Output
Subintensity matrix:
[,1] [,2] [,3]
[1,] -3 2 0
[2,] 0 -2 1
[3,] 0 0 -1
Reward matrix:
[,1] [,2]
[1,] 4.4 4.3
[2,] 2.0 1.8
[3,] 8.8 2.3
Initial probabilities:
[,1] [,2] [,3]
[1,] 1 0 0
Defect:
[1] 0
Means:
[1] 5.066667 2.800000
Variance-covariance matrix:
[,1] [,2]
[1,] 48.01778 15.282222
[2,] 15.28222 6.173333
Code
summary(MDPH(subint_mat = matrix(c(0.4, 0.24, 0.12, 0, 0.4, 0.2, 0, 0, 0.5),
ncol = 3, byrow = TRUE), reward_mat = matrix(c(4, 2, 8, 4, 1, 2), nrow = 3,
ncol = 2), init_probs = c(1, 0, 0)))
Output
Subintensity matrix:
[,1] [,2] [,3]
[1,] 0.4 0.24 0.12
[2,] 0.0 0.40 0.20
[3,] 0.0 0.00 0.50
Reward matrix:
[,1] [,2]
[1,] 4 4
[2,] 2 1
[3,] 8 2
Initial probabilities:
[,1] [,2] [,3]
[1,] 1 0 0
Defect:
[1] 0
Means:
[1] 13.333333 8.666667
Variance-covariance matrix:
[,1] [,2]
[1,] 121.77778 44.88889
[2,] 44.88889 25.11111
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