A unified approach is suggested to estimate the population size for continuous time capture studies with possible removals during the capture process. It extends and improves the Lin-Yip estimator. The usual recapture and removal models can be shown to be particular cases of the general formulation. A Horvitz-Thompson procedure is used to estimate the population size based on the estimated capture probabilities. The resultant estimators for the regression parameters and population size are consistent and asymptotically normal under appropriate regularity conditions. We assess the properties of the proposed estimators through Monte Carlo simulation. Two examples are given. © 2002 American Statistical Association and the International Biometr...
[[abstract]]This article reviews various models for both discrete-time and continuous-time closed ca...
A continuous time frailty capture-recapture model is proposed for estimating population size of a cl...
Schofield et al. (2018, Biometrics 74, 626–635) presented simple and efficient algorithms for fittin...
A unified approach is suggested to estimate the population size for a closed population in discrete ...
We use a class of parametric counting process regression models that are commonly employed in the an...
A two-step procedure based on a partial likelihood is proposed to estimate the size of a closed popu...
[[abstract]]An estimation procedure using the idea of sample coverage is proposed to estimate popula...
Abstract: Estimation methods are suggested to estimate the population size in pro-portional trapping...
We use martingale theory and a method of moments technique to derive a class of estimators for the s...
We use the semiparametric additive hazards model to formulate the effects of individual covariates o...
A semiparametric estimation procedure is proposed to model capture-recapture data with the aim of es...
Estimation methods are suggested to estimate the population size in proportional trapping removal an...
Conditional likelihood based on counting processes are combined with a Horvitz-Thompson estimator to...
A continuous time frailty capture-recapture model is proposed for estimating population size of a cl...
This paper investigates the applications of capture-recapture methods to human populations. Capture-...
[[abstract]]This article reviews various models for both discrete-time and continuous-time closed ca...
A continuous time frailty capture-recapture model is proposed for estimating population size of a cl...
Schofield et al. (2018, Biometrics 74, 626–635) presented simple and efficient algorithms for fittin...
A unified approach is suggested to estimate the population size for a closed population in discrete ...
We use a class of parametric counting process regression models that are commonly employed in the an...
A two-step procedure based on a partial likelihood is proposed to estimate the size of a closed popu...
[[abstract]]An estimation procedure using the idea of sample coverage is proposed to estimate popula...
Abstract: Estimation methods are suggested to estimate the population size in pro-portional trapping...
We use martingale theory and a method of moments technique to derive a class of estimators for the s...
We use the semiparametric additive hazards model to formulate the effects of individual covariates o...
A semiparametric estimation procedure is proposed to model capture-recapture data with the aim of es...
Estimation methods are suggested to estimate the population size in proportional trapping removal an...
Conditional likelihood based on counting processes are combined with a Horvitz-Thompson estimator to...
A continuous time frailty capture-recapture model is proposed for estimating population size of a cl...
This paper investigates the applications of capture-recapture methods to human populations. Capture-...
[[abstract]]This article reviews various models for both discrete-time and continuous-time closed ca...
A continuous time frailty capture-recapture model is proposed for estimating population size of a cl...
Schofield et al. (2018, Biometrics 74, 626–635) presented simple and efficient algorithms for fittin...