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利用贝叶斯树形捕获再捕获模型构造后分层AI 解读

For the problem of dual system estimation, we propose a Bayesian treed capture-recapture model to account for heterogeneity of capture probabilities where individual auxiliary information is available. The model uses a binary tree to partition the covariate space into ‘homogeneous’ regions, within each of which the capture response can be described adequately by a simple model that assumes equal catchability. The attractive features of the proposed model include reduction of…

排序集样本的刻画及其在分布函数估计中的应用AI 解读

Ranked-set sampling has been shown to provide improved estimators of the mean and variance when actual measurement of the observations is difficult but ranking of the elements in a sample is relatively easy. This result holds even if the ranking is imperfect. In this article, we provide a characterization of a ranked-set sample that makes the source of this additional information intuitively clear. It is applied to show that the empirical distribution function of a…

复杂调查中访问员方差实验的最优设计AI 解读

Fellegi's (1974) improved method for estimating the interviewer component of correlated response variance is extended to l groups of k interviewer assignments for general multistage survey designs. Using a linear models approach suggestive of Hartley and Rao's (1978), the independence of the two estimators of interviewer variance is established and the forms of the variances of the estimators are derived. Then using 1980 census data to compute terms in the estimator…

复杂调查中访员方差实验的最优设计AI 解读

Fellegi's (1974) improved method for estimating the interviewer component of correlated response variance is extended to l groups of k interviewer assignments for general multistage survey designs. Using a linear models approach suggestive of Hartley and Rao's (1978), the independence of the two estimators of interviewer variance is established and the forms of the variances of the estimators are derived. Then using 1980 census data to compute terms in the estimator…

基于排序集样本的二元正态总体相关系数推断AI 解读

Ranked set sampling was first used to obtain an improved estimate of a population mean. This technique is useful when a small random sample can be visually ordered easily and fairly accurately, but exact measurement of an observation is difficult or expensive. The sampling method is generalized and applied to estimation of the correlation coefficient ρ of a bivariate normal random vector (X, Y). The asymptotic variance of the maximum likelihood estimator of ρ based only on…