| inla.knmodels.sample {INLA} | R Documentation |
Spacetime interaction models sampler function
Description
It implements the sampling method for the models in Knorr-Held, L. (2000) considering the algorithm 3.1 in Rue & Held (2005) book.
Usage
inla.knmodels.sample(
graph,
m,
type = 4,
intercept = 0,
tau.t = 1,
phi.t = 0.7,
tau.s = 1,
phi.s = 0.7,
tau.st = 1,
ev.t = NULL,
ev.s = NULL
)
Arguments
graph |
Model graph definition |
m |
Time dimention. |
type |
Integer from 1 to 4 to identify one of the four interaction type. |
intercept |
A constant to be added to the linear predictor |
tau.t |
Precision parameter for the main temporal effect. |
phi.t |
Mixing parameter in the |
tau.s |
Precision parameter for the main spatial effect. |
phi.s |
Mixing parameter in the |
tau.st |
Precision parameter for the spacetime effect. |
ev.t |
Eigenvalues and eigenvectors of the temporal precision matrix structure. |
ev.s |
Eigenvalues and eigenvectors of the spatial precision matrix structure. |
Value
A list with the following elements
time |
The time index for
each obervation, with length equals |
space |
The spatial index for
each observation, with length equals |
spacetime |
The spacetime
index for each obervation, with length equals |
x |
A list with the following elements |
t.iid |
The unstructured main temporal effect part. |
t.str |
The structured main temporal effect part. |
t |
The
main temporal effect with length equals |
s.iid |
The unstructured main spatial effect part. |
s.str |
The structured main spatial effect part. |
s |
The main spatial effect with length equals |
st |
The spacetime interaction effect with length |
eta |
The linear predictor with length |
Author(s)
Elias T. Krainski
See Also
inla.knmodels() for model fitting