Description Usage Format Examples

inherit from class `SimYuima`

dX = X (r - C X + M X / (1 + h M X)) dt + Sigma dW
X (r - C X + M X / (1 + h M X)) is the drift vector,
which include:
r - vector of intrinsic growth rates
C - competitive interactions matrix, all self-regulation strength is [s], all inter-species competitive strength is [c]
M - mutualistic interactions matrix
h - handling time
Note: we only support mean field approximation
Note: we only support the bipartite network of mutualistic interactions
Sigma is the diffusion matrix, we assume it's a diagonal matrix
W is a vector of Wiener process

1 |

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ```
Class 'R6ClassGenerator' <SimSlv2> object generator
Inherits from: <SimYuima>
Public:
r: 0
delta: 0
sigma: 0.02
rmin: NULL
set_drift: function (n1, n2)
set_diffusion: function (n)
set_variables: function (n)
set_params: function (n1, n2, r, delta, s, c, h, M, sigma)
sim: function (n1, n2, r, delta, s, c, h, M, sigma, steps, stepwise,
clone: function (deep = FALSE)
Parent env: <environment: namespace:StabEco>
Locked objects: TRUE
Locked class: FALSE
Portable: TRUE
- attr(*, "name")= chr "SimSlv2_generator"
``` |

1 2 3 4 5 6 7 8 9 10 | ```
simSLV2 <- SimSLV2$new()
simSLV2$set_drift(n1 = 1, n2 = 2)
simSLV2$set_diffusion(n = 1+2)
simSLV2$set_variables(n = 1+2)
simSLV2$set_model()
simSLV2$set_times(steps = 1000, stepwise = 1)
simSLV2$set_init(xinit = c(1,1,1))
simSLV2$set_params(n1 = 1, n2 = 2, r = 1, delta = 0.001, s = 1, c = 0.01, h = 0.5, M = 1 * matrix(c(0, 1, 1, 1, 0, 0, 1, 0, 0), ncol = 3), sigma = 0.01)
simSLV2$simulate()
out = simSLV2$get_out()
``` |

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