用于从不确知植物捕获估计种群规模的植物捕获方法
Plant-Capture Methods for Estimating Population Size from Uncertain Plant Captures
AI总结：
本文提出植物捕获模型的新推断方法，以处理捕获状态不确定性和地点异质性，并应用于美国城市无家可归人口规模估计。
摘要：
植物捕获是经典捕获-再捕获方法的一种变体，用于估计种群规模。在该方法中，被称为“植物”的诱饵被引入种群，以估计捕获概率。该方法在许多流行病学、生态学和人口学研究中，从有限样本估计种群规模方面已显示出相当大的成功。然而，以往的植物再捕获研究并未系统地考虑每株植物捕获状态的不确定性。在本工作中，我们提出了多种方法，以正式地将不确定性纳入植物捕获模型，这些不确定性源于（i）植物的捕获状态和（ii）多个调查地点之间的异质性。我们提出了两种推断方法，并在模拟研究中比较了它们的性能。随后，我们将我们的方法应用于使用美国人口普查局开展的大规模“S-night”研究来估计美国几个城市的无家可归人口规模。
英文摘要：
Plant-capture is a variant of classical capture-recapture methods used to estimate the size of a population. In this method, decoys referred to as "plants" are introduced into the population in order to estimate the capture probability. The method has shown considerable success in estimating population sizes from limited samples in many epidemiological, ecological, and demographic studies. However, previous plant-recapture studies have not systematically accounted for uncertainty in the capture status of each individual plant. In this work, we propose various approaches to formally incorporate uncertainty into the plant-capture model arising from (i) the capture status of plants and (ii) the heterogeneity between multiple survey sites. We present two inference methods and compare their performance in simulation studies. We then apply our methods to estimate the size of the homeless population in several US cities using the large-scale "S-night" study conducted by the US Census Bureau.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
