mpmm | R Documentation |
Fit a move persistence random walk via TMB to a pre-filtered/regularized animal track and estimate gamma as a linear function of covariates
mpmm(
formula = NA,
data = NULL,
map = NULL,
control = mpmm_control(),
inner.control = inner_control()
)
formula |
a right-hand-side regression formula (no response variable) |
data |
a data frame of observations (see details) |
map |
a named list of parameters as factors that are to be fixed during estimation, e.g., list(rho = factor(NA)) |
control |
a list of control parameters for the outer optimization
(see |
inner.control |
a list of control parameters for the inner optimization
(see |
The input track is given as a dataframe where each row is an observed location and columns
individual animal identifier,
observation time (POSIXct,GMT),
observed longitude,
observed latitude,
identifier for tracks if there are more than one track per individual (optional),
named covariates appended to track
a list with components
states |
a dataframe of estimated states |
fitted |
a dataframe of fitted locations |
par |
model parameter summmary |
data |
input dataframe |
tmb |
the tmb object |
opt |
the object returned by the optimizer |
data(ellie.ice.short)
fit <- mpmm(~ ice + (1 | id), data = ellie.ice.short)
summary(fit)
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