Description Usage Arguments Details Value Author(s) References
Fits local loglinear models. Each distinct covariate vector gets its own model. To reduce the number of models, some rounding of continuous covariates is done first.
1 2 3 
dat 
Capturerecapture data, as output of 
kfrac 
The approximate fraction of the data that is included in the support of the kernel for the local averages. 
models 
A list of models – or an expression that returns a
list of models – to be considered in local model search. The default is 
ic 
The information criterion for selection of local loglinear models. The default, BICpi, appears in Hook and Regal (1997). 
bw 
A singlecolumn matrix with rownames that match the covariate
names in 
averaging 
Logical: Should model averaging be done for each local model? 
cell.adj 
Logical: Whether to adjust the cells as in Evans and Bonett (1994). TRUE by default. 
round.vars 
See 
rounding.scale 
See 
boot.control 
A list of control parameters for bootstrapping the sampling distribution of the estimator(s). By default, there is no bootstrapping. 
The key implementation of the thesis of Kurtz 2013, Carnegie Mellon University
est 
A point estimate of the population size 
llform 
The set of loglinear terms 
dat 
The output of function

ess 
The local effective sample sizes that are based on the local averaging weights and used as eta_i in local model selection 
hpi 
The matrix of local averages 
... 
The output is of class

Zach Kurtz
Kurtz ZT (2013). "Smooth PostStratification for Multiple CaptureRecapture." arXiv preprint arXiv:1302.0890.
Anderson DR and Burnham KP (1999). "Understanding information criteria for selection among capturerecapture or ring recovery models." Bird Study, 46(S1), pp. S14S21.
Fienberg SE (1972). "The Multiple Recapture Census for Closed Populations and Incomplete $2^k$ Contingency Tables." Biometrika, 59(3), pp. 591.
Evans MA and Bonett DG (1994). "Bias Reduction for MultipleRecapture Estimators of Closed Population Size." Biometrics, 50(2), pp. 388395.
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