Incorporating multiple samples for estimation is becoming increasingly popular across industries and disciplines. Indeed, various fisheries agencies combine samples when estimating catch totals. In this paper, we examine a probabilistic matching technique to link a non-probability sample of electronic reports of fishing trips with a dockside probability sample. We use 2017 data from a capture-recapture pilot study in the Gulf of Mexico and compare it with current methodologies. We also examine a key parameter used in record linkage—a threshold score for the algorithm—and study its effect in this setting. We show that combining non-probability data with a probability sample is useful for estimating fish catch and argue record linkage is a useful way to link the data.

合并多个样本进行估计在各个行业和学科中变得越来越流行。事实上，各种渔业机构在估算总渔获量时会合并样本。在本文中，我们研究了一种概率匹配技术，将钓鱼旅行电子报告的非概率样本与码头概率样本联系起来。我们使用了 2017 年墨西哥湾捕捞-再捕捞试点研究的数据，并将其与当前方法进行比较。我们还检查了记录链接中使用的一个关键参数——算法的阈值分数——并研究了它在此设置中的效果。我们表明，将非概率数据与概率样本相结合对于估计渔获量很有用，并认为记录链接是链接数据的有用方法。