inla.knmodels.sample {INLA} | R Documentation |
It implements the sampling method for the models in Knorr-Held, L. (2000) considering the algorithm 3.1 in Rue & Held (2005) book.
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 )
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. |
A list with the following elements
time |
The time index for each obervation, with length equals mn. \itemspaceThe spatial index for each obervation, with length equals mn. |
spacetime |
The spacetime index for each obervation, with length equals m*n. |
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 2m. |
s.iid |
The unstructured main spatial effect part. |
s.str |
The structured main spatial effect part. |
s |
The main spatial effect with length equals 2n. |
st |
The spacetime interaction effect with length |
eta |
The linear predictor with length |
Elias T. Krainski
inla.knmodels
for model fitting