In this paper we attempt to answer the following question: ``Is it possible to obtain reliable estimates for the prevalence of anemia rates in children under five years in the districts of Peru?'' Specifically, the interest of the present paper is to understand to which extent employing the basic and the spatial Fay-Herriot models can compensate for inadequate sample size in most of the sampled districts, and whether the way of choosing the spatial neighbors has an impact on the resulting inference. Furthermore, it is raised the question of how to choose an optimal way to define the neighbours. We present an illustrative analysis using the data from the Demographic and Family Health Survey of the year 2019, and the National Census carried out in 2017.

中文翻译：

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以小样本量估计秘鲁地区五岁以下儿童的贫血率

在本文中，我们试图回答以下问题：“是否有可能获得秘鲁地区五岁以下儿童贫血率的可靠估计值？”具体而言，本文的目的是了解使用基本和空间 Fay-Herriot 模型在多大程度上可以弥补大多数抽样区域的样本量不足，以及选择空间邻居的方式是否对由此产生的推断产生影响。此外，还提出了如何选择最佳方式来定义邻居的问题。我们使用来自 2019 年人口和家庭健康调查以及 2017 年进行的全国人口普查的数据进行说明性分析。