| algo.hhh.grid {surveillance} | R Documentation |
Tries multiple starting values in algo.hhh.
Starting values are provided in a matrix with gridSize rows, the
grid search is conducted until either all starting values are used or
a time limit maxTime is exceeded.
The result with the highest likelihood is returned.
algo.hhh.grid(disProgObj, control=list(lambda=TRUE, neighbours=FALSE,
linear=FALSE, nseason=0,
negbin=c("none", "single", "multiple"),
proportion=c("none", "single", "multiple")),
thetastartMatrix, maxTime=1800, verbose=FALSE)
disProgObj |
Object of class disProg |
control |
Control object:
|
thetastartMatrix |
matrix with initial values for all parameters specified in the control object as rows. |
verbose |
if true progress information is printed |
maxTime |
maximum of time (in seconds) to elapse until algorithm stopps. |
list |
|
M. Paul, L. Held
Held, L., Höhle, M., Hofmann, M. (2005) A statistical framework for the analysis of multivariate infectious disease surveillance counts. Statistical Modelling, 5, p. 187–199.
meanResponse,create.grid,algo.hhh
## monthly counts of menigococcal infections in France
data(meningo.age)
# specify model for algo.hhh.grid
model1 <- list(lambda=TRUE)
# create grid of inital values
grid1 <- create.grid(meningo.age, model1,
params = list(epidemic=c(0.1,0.9,5)))
# try multiple starting values, print progress information
algo.hhh.grid(meningo.age, control=model1, thetastartMatrix=grid1,
verbose=TRUE)
# specify model
model2 <- list(lambda=TRUE, neighbours=TRUE, negbin="single",
nseason=1)
grid2 <- create.grid(meningo.age, model2,
params = list(epidemic=c(0.1,0.9,3),
endemic=c(-0.5,0.5,3),
negbin = c(0.3, 12, 10)))
# run algo.hhh.grid, search time is limited to 30 sec
algo.hhh.grid(meningo.age, control=model2, thetastartMatrix=grid2,
maxTime=30)
## weekly counts of influenza and meningococcal infections in Germany, 2001-2006
data(influMen)
# specify model with two autoregressive parameters lambda_i, overdispersion
# parameters psi_i, an autoregressive parameter phi for meningococcal infections
# (i.e. nu_flu,t = lambda_flu * y_flu,t-1
# and nu_men,t = lambda_men * y_men,t-1 + phi_men*y_flu,t-1 )
# and S=(3,1) Fourier frequencies
model <- list(lambda=c(TRUE,TRUE), neighbours=c(FALSE,TRUE),
linear=FALSE, nseason=c(3,1),negbin="multiple")
# create grid of initial values
grid <- create.grid(influMen,model, list(epidemic=c(.1,.9,3),
endemic=c(-.5,.5,3), negbin=c(.3,15,10)))
# run algo.hhh.grid, search time is limited to 30 sec
algo.hhh.grid(influMen, control=model, thetastartMatrix=grid, maxTime=30)