sfilter
fit the state-space model to data after passing through prefilter
Description
generates 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
Usage
sfilter(
x,
model = c("rw", "crw"),
time.step = 6,
scale = FALSE,
parameters = NULL,
map = NULL,
fit.to.subset = TRUE,
control = ssm_control(),
inner.control = NULL
)Arguments
x |
Argos data passed through prefilter() |
model |
specify which SSM is to be fit: "rw" or "crw" |
time.step |
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 |
scale location data for more efficient optimization. |
parameters |
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... |
map |
a named list of parameters as factors that are to be fixed during estimation, e.g., list(psi = factor(NA)) |
fit.to.subset |
fit the SSM to the data subset determined by prefilter (default is TRUE) |
control |
list of control parameters for the outer optimization (see |
inner.control |
list of control settings for the inner optimization (see ?TMB::MakeADFUN for additional details) |
verbose |
|
optim |
|
optMeth |
|
lpsi |
|
![[Deprecated]](../help/figures/lifecycle-deprecated.svg)
Details
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).