We describe a new class of capture-recapture models for closed populations when individual covariates are available. The novelty consists in combining a latent class model where the marginal weights and the conditional distributions given the latent may depend on covariates, with a model for the marginal distribution of the available covariates. In addition, a general formulation for the conditional distributions given the latent which allows serial dependence is provided. An efficient algorithm for maximum likelihood estimation is presented, asymptotic results are derived, and a procedure for constructing likelihood based confidence intervals for the population total is presented. Two examples with real data are used to illustrate the proposed approach.
翻译:我们描述了在个别共变情况存在时对封闭人口采用一种新的捕捉-抓获模式类别,新颖之处在于将潜在类别模式(即边际加权数和潜在值的有条件分布值可能取决于共变情况)与现有共变数的边际分布模式结合起来,此外,根据允许序列依赖的潜值,对有条件分布作了一般性的表述;提出了尽可能估计可能性的有效算法,得出了无症状结果,并提出了为人口总数建立基于可能性的信任间隔的程序;用两个有真实数据的例子来说明拟议办法。