prefiltergenerates initial values for model parameters and unobserved states;
structures data and initial values for C++ TMB template;
fits state-space model; minimizes the joint log-likelihood via the selected
optimizer (nlminb or optim); structures and passes output
object to fit_ssm
sfilter(
x,
model = c("rw", "crw"),
time.step = 6,
scale = FALSE,
parameters = NULL,
map = NULL,
fit.to.subset = TRUE,
optim = c("nlminb", "optim"),
optMeth = c("L-BFGS-B", "BFGS", "Nelder-Mead", "CG", "SANN", "Brent"),
verbose = 1,
control = NULL,
inner.control = NULL,
lpsi = -10
)Argos data passed through prefilter()
specify which SSM is to be fit: "rw" or "crw"
the regular time interval, in hours, to predict to. Alternatively, a vector of prediction times, possibly not regular, must be specified as a data.frame with id and POSIXt dates.
scale location data for more efficient optimization.
a list of initial values for all model parameters and unobserved states, default is to let sfilter specify these. Only play with this if you know what you are doing...
a named list of parameters as factors that are to be fixed during estimation, e.g., list(psi = factor(NA))
fit the SSM to the data subset determined by prefilter (default is TRUE)
numerical optimizer to be used ("nlminb" or "optim")
optimization method to use (default is "L-BFGS-B"), ignored if optim = "nlminb"
report progress during minimization (0 = silent; 1 = show parameter trace [default]; 2 = show optimizer trace)
list of control parameters for the outer optimization (type ?nlminb or ?optim for details)
list of control settings for the inner optimization (see ?TMB::MakeADFUN for additional details)
lower bound for the psi parameter
called by fit_ssm, not intended for general use. sfilter can only fit to an
individual track, use fit_ssm to fit to multiple tracks (see ?fit_ssm).