A function that estimates sizes of specific sub populations based on a capture-recapture model for the whole population.
stratifyPopsize(object, strata, alpha, ...)# S3 method for singleRStaticCountData
stratifyPopsize(object, strata, alpha, cov = NULL, ...)
A data.frame object with row names being the names of specified
sub populations either provided or inferred.
an object on which the population size estimates should be based
in singleRcapture package this is a fitter singleRStaticCountData class object.
a specification of sub populations given by one of:
formula -- a formula to be applied to model.frame extracted from
the object.
Logical vector with number of entries equal to number of rows in the dataset.
A (named) list where each element is a logical vector, names of the list will be used to specify names variable in returned object.
Vector of names of explanatory variables. For singleRStaticCountData method
for this function this specification of strata parameter will
result in every level of explanatory variable having its own sub population
for each variable specified.
If no value was provided the singleRStaticCountData method for this function
will itself create sub populations based on levels of factor variables
in model.frame.
significance level for confidence intervals --
Either a single numeric value or a vector of length equal to number of
sub populations specified in strata.
If missing it is set to .05 in singleRStaticCountData method.
a vector of arguments to be passed to other functions.
For singleRStaticCountData method for this functions arguments in ... are
passed to either cov if argument provided was a function or
vcov if cov argument was missing at call.
for singleRStaticCountData method an estimate of variance-covariance matrix
for estimate of regression parameters. It is possible to pass a function
such as for example sandwich::vcovHC which will be called as:
foo(object, ...) and a user may specify additional arguments of a
function in ... argument. If not provided an estimate for covariance
matrix will be set by calling appropriate vcov method.
In single source capture-recapture models the most frequently used estimate for population size is Horvitz-Thompson type estimate:
N = _k=1^NI_kP(Y_k>0) = _k=1^N_obs11-P(Y_k=0)
where I_k=I_Y_k > 0 are indicator variables, with value 1 if kth unit was observed at least once and 0 otherwise and the inverse probabilistic weights weights for units observed in the data 1P(Y_k>0) are estimated using fitted linear predictors.
The estimates for different sub populations are made by changing the I_k=I_Y_k > 0 indicator variables to refer not to the population as a whole but to the sub populations that are being considered i.e. by changing values from 1 to 0 if kth unit is not a member of sub population that is being considered at the moment.
The estimation of variance for these estimates and estimation of variance for estimate of population size for the whole population follow the same relation as the one described above.
vcov.singleRStaticCountData() estimatePopsize()