• Corpus ID: 244117436

drpop: Efficient and Doubly Robust Population Size Estimation in R

@inproceedings{Das2021drpopEA,
  title={drpop: Efficient and Doubly Robust Population Size Estimation in R},
  author={Manjari Das and Edward H. Kennedy},
  year={2021}
}
This paper introduces the R package drpop to flexibly estimate total population size from incomplete lists. Total population estimation, also called capture-recapture, is an important problem in many biological and social sciences. A typical dataset consists of incomplete lists of individuals from the population of interest along with some covariate information. The goal is to estimate the number of unobserved individuals and equivalently, the total population size. drpop flexibly models… 

Figures and Tables from this paper

References

SHOWING 1-10 OF 73 REFERENCES
Doubly robust capture-recapture methods for estimating population size
Estimation of population size using incomplete lists (also called the capture-recapture problem) has a long history across many biological and social sciences. For example, human rights groups often
Estimation of population size based on capture recapture designs and evaluation of the estimation reliability
We propose a modern method to estimate population size based on capture-recapture designs of K samples. The observed data is formulated as a sample of n i.i.d. K-dimensional vectors of binary
The VGAM Package for Capture-Recapture Data Using the Conditional Likelihood
TLDR
This work presents several new R functions specifically developed to allow the incorporation of individual covariates in the analysis of closed population CR data using a GLM/GAM-like approach and the conditional likelihood.
Non‐parametric estimation of population size from capture–recapture data when the capture probability depends on a covariate
In capture-recapture experiments the capture probabilities may depend on individual covariates such as an individual's weight or age. Typically this dependence is modelled through simple parametric
Inference for Poisson and multinomial models for capture-recapture experiments
SUMMARY Capture-recapture models have been formulated both as Poisson and as multinomial distributions. Maximum likelihood estimates of parameters under the two models are compared. For parameters
The applications of capture-recapture models to epidemiological data.
TLDR
This tutorial reviews various closed capture-recapture models which are applicable to ascertainment data for estimating the size of a target population based on several incomplete lists of individuals and introduces three approaches and their associated estimation procedures.
The use of auxiliary variables in capture-recapture modelling: An overview
I review the use of auxiliary variables in capture-recapture models for estimation of demographic parameters (e.g. capture probability, population size, survival probability, and recruitment,
A unified approach for estimating population size in capture-recapture studies with arbitrary removals
A unified approach is suggested to estimate the population size for a closed population in discrete time. Individuals can be removed after capture at any time during the experiment. The usual
A survey of software for fitting capture–recapture models
TLDR
A survey of software programs aimed primarily at estimating the total size of a population, based on three different perspectives: types of classical closed-population models, statistical foundations or philosophy, and extensions or variations of classical models.
Robust Estimation of Population Size When Capture Probabilities Vary Among Animals
TLDR
A model is given for multiple recapture studies on closed populations which allows capture probabilities to vary among individuals and a nonparametric estimation procedure for population size is given that is robust to moderate variations in individual capture probabilities which may occur in commonly used short—term livetrapping studies.
...
1
2
3
4
5
...