popsize_cond {drpop}  R Documentation 
Estimate total population size and capture probability using user provided set of models conditioned on an attribute.
popsize_cond(
data,
K = 2,
filterrows = FALSE,
funcname = c("rangerlogit"),
condvar,
nfolds = 2,
margin = 0.005,
sl.lib = c("SL.gam", "SL.glm", "SL.glm.interaction", "SL.ranger", "SL.glmnet"),
TMLE = TRUE,
PLUGIN = TRUE,
Nmin = 100,
...
)
data 
The data frame in capturerecapture format for which total population is to be estimated. The first K columns are the capture history indicators for the K lists. The remaining columns are covariates in numeric format. 
K 
The number of lists in the data. typically the first 
filterrows 
A logical value denoting whether to remove all rows with only zeroes. 
funcname 
The vector of estimation function names to obtain the population size. 
condvar 
The covariate for which conditional estimates are required. 
nfolds 
The number of folds to be used for cross fitting. 
margin 
The minimum value the estimates can attain to bound them away from zero. 
sl.lib 
Algorithm library for 
TMLE 
The logical value to indicate whether TMLE has to be computed. 
PLUGIN 
The logical value to indicate whether the plugin estimates are returned. 
Nmin 
The cutoff for minimum sample size to perform doubly robust estimation. Otherwise, Petersen estimator is returned. 
... 
Any extra arguments passed into the function. See 
A list of estimates containing the following components for each listpair, model and method (PI = plugin, DR = doublyrobust, TMLE = targeted maximum likelihood estimate):
result 
A dataframe of the below estimated quantities.

N 
The number of data points used in the estimation after removing rows with missing data. 
ifvals 
The estimated influence function values for the observed data. 
nuis 
The estimated nuisance functions (q12, q1, q2) for each element in funcname. 
nuistmle 
The estimated nuisance functions (q12, q1, q2) from tmle for each element in funcname. 
idfold 
The division of the rows into sets (folds) for crossfitting. 
Das, M., Kennedy, E. H., & Jewell, N.P. (2021). Doubly robust capturerecapture methods for estimating population size. arXiv preprint arXiv:2104.14091.
data = simuldata(n = 10000, l = 2, categorical = TRUE)$data
psin_estimate = popsize_cond(data = data, funcname = c("logit", "gam"),
condvar = 'catcov', PLUGIN = TRUE, TMLE = TRUE)
#this returns the plugin, the biascorrected and the tmle estimate for the
#two models conditioned on column catcov