SimInf_model {SimInf} | R Documentation |
SimInf_model
Create a SimInf_model
SimInf_model(G, S, tspan, events = NULL, ldata = NULL, gdata = NULL, U = NULL, u0 = NULL, v0 = NULL, V = NULL, E = NULL, N = NULL, C_code = NULL)
G |
Dependency graph that indicates the transition rates that
need to be updated after a given state transition has occured.
A non-zero entry in element |
S |
Each column corresponds to a transition, and execution of
state transition |
tspan |
A vector (length >= 2) of increasing time points
where the state of each node is to be returned. Can be either
an |
events |
A |
ldata |
A matrix with local data for the nodes. The column
|
gdata |
A numeric vector with global data that is common to all nodes. The global data vector is passed as an argument to the transition rate functions and the post time step function. |
U |
The result matrix with the number of individuals in each
disease state in every node (N_n N_c \times
|
u0 |
The initial state vector. Either a matrix (N_c
\times N_n) or a a |
v0 |
The initial continuous state vector in every node.
( |
V |
The result matrix for the real-valued continous
compartment state (N_n |
E |
Sparse matrix to handle scheduled events, see
|
N |
Sparse matrix to handle scheduled events, see
|
C_code |
Character vector with optional model C code. If
non-empty, the C code is written to a temporary C-file when
the |