mark(data, ddl = NULL, begin.time = 1, model.name = NULL, model = "CJS",
title = "", model.parameters = list(), initial = NULL,
design.parameters = list(), right = TRUE, groups = NULL,
age.var = NULL, initial.ages = 0, age.unit = 1, time.intervals = NULL,
nocc = NULL, output = TRUE, invisible = TRUE, adjust = TRUE,
mixtures = 1, se = FALSE, filename = NULL, prefix = "mark",
default.fixed = TRUE, silent = FALSE, retry = 0, options = NULL,
brief = FALSE, realvcv = FALSE, delete = FALSE, external = FALSE,
profile.int = FALSE, chat = NULL, reverse = FALSE, run = TRUE,
input.links = NULL, parm.specific = FALSE, mlogit0 = FALSE,
threads = -1, hessian = FALSE, accumulate = TRUE, allgroups = FALSE,
strata.labels = NULL, counts = NULL, icvalues = NULL)
groups
even if there are no observations in the
grouprerun.mark
index
is
the parameter index in the full parameter structure and value
is the
fixed value for the real parameterpim.translation
which
translate between all different and simplified pims, real.labels
which are labels for real parameters for full (non-simplified) pim structure
and links
the link function names for the full parameter structurelnl
-2xLog Likelihood value
npar
Number of parameters (always the number of columns in
design matrix)
npar.unadjusted
number of estimated
parameters from MARK if different than npar
n
effective
sample size
AICc
Small sample corrected AIC using npar
AICc.unadjusted
Small sample corrected AIC using
npar.unadjusted
beta
data frame of beta parameters with
estimate, se, lcl, ucl
real
data frame of real
parameters with estimate, se, lcl, ucl and fixed
beta.vcv
variance-covariance matrix for beta
derived
dataframe of derived parameters if any
derived.vcv
variance-covariance matrix for derived parameters if any
covariate.values
dataframe with fields Variable
and
Value
which are the covariate names and value used for
real parameter
estimates in the MARK output
singular
indices of beta parameters that are non-estimable or at
a boundary
real.vcv
variance-covariance matrix for real
parameters (simplified) if realvcv=TRUE
}model.parameters
) for each of the parameters in the
capture-recapture model being fitted to the data. It runs MARK.EXE (see note
below) and then imports the text output file and binary variance-covariance
file that were created. It extracts output values from the text file and
creates a list of results that is returned as part of the list (of class
mark) which is the return value for this function.
The models that are currently supported are listed in MarkModels.pdf which
you can find in the RMark sub-directory of your R Library. Also, they are
listed under Help/Data Types in the MARK interface.
The function mark is a shell that calls 5 other functions in the following
order as needed: 1) process.data
, 2)
make.design.data
, 3) make.mark.model
, 4)
run.mark.model
, and 5) summary.mark
. A MARK
model can be fitted with this function (mark
) or by calling the
individual functions that it uses. The calling arguments for mark
are a compilation of the calling arguments for each of the functions it
calls (with some arguments renamed to avoid conflicts). If data is a
processed dataframe (see process.data
) then it expects to find
a value for ddl
. Likewise, if the data have not been processed, then
ddl
should be NULL. This dual calling structure allows either a
single call approach for each model or alternatively for the data to be
processed and the design data (ddl
) to be created once and then a
whole series of models can be analyzed without repeating those steps.
For descriptions of the arguments data
, begin.time
,
groups
, age.var
, initial.ages
, age.unit
,
time.intervals
and mixtures
see process.data
.
For descriptions of ddl
, design.parameters
=parameters
,
and right
, see make.design.data
.
For descriptions of model.name
, model
,
title
,model.parameters
=parameters
,
default.fixed
, initial
, options
, see
make.mark.model
.
And finally, for descriptions of arguments invisible
, filename
and adjust
,see run.mark.model
.
output
,silent
, and retry
are the only arguments
specific to mark. output
controls whether a summary of the model
input and output are given(if output=TRUE
). silent
controls
whether errors are shown when fitting a model. retry
controls the
number of times a model will be refitted with new starting values (uses 0)
when some parameters are determined to be non-estimable or at a boundary.
The latter is the only time it makes sense to retry with new starting values
but MARK cannot discern between these two instances. The indices of the beta
parameters that are "singular" are stored in results$singular
.make.mark.model
, run.mark.model
,
make.design.data
, process.data
,
summary.mark
data(dipper)
dipper.Phidot.pdot=mark(dipper,threads=1)
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