Small area estimation for semicontinuous skewed spatial data: An application to the grape wine production in Tuscany
Small area estimation for semicontinuous skewed spatial data: An application to the grape wine production in Tuscany
复制标题
半连续偏斜空间数据的小面积估计：在托斯卡纳葡萄酒生产中的应用
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
E. Rocco
中科院分区：
文献类型：
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作者：
E. Dreassi;A. Petrucci;E. Rocco
在小面积估计（SAE）问题中，经常使用线性混合模型来获得基于模型的估计量。然而，当目标变量的点质量为零、非零值的分布高度偏斜、空间结构强时，这种模型就不适用了。本文提出了一种处理此类变量的SAE方法。我们提出了一个两部分随机效应SAE模型，该模型包括两部分中出现的区域随机效应的相关结构，并结合了单位地理坐标的二元平滑函数。为了考虑响应变量正值分布的偏性，采用Gamma模型。为了拟合模型，获得小面积估计并评估其精度，使用了层次贝叶斯方法。这项研究的动机是一个真正的SAE问题。我们主要利用农场结构调查数据，在分区域水平上估计托斯卡纳每个农场的平均葡萄酒产量。实际数据应用和基于模型的仿真实验结果表明，所提出的SAE方法具有令人满意的性能。
Linear‐mixed models are frequently used to obtain model‐based estimators in small area estimation (SAE) problems. Such models, however, are not suitable when the target variable exhibits a point mass at zero, a highly skewed distribution of the nonzero values and a strong spatial structure. In this paper, a SAE approach for dealing with such variables is suggested. We propose a two‐part random effects SAE model that includes a correlation structure on the area random effects that appears in the two parts and incorporates a bivariate smooth function of the geographical coordinates of units. To account for the skewness of the distribution of the positive values of the response variable, a Gamma model is adopted. To fit the model, to get small area estimates and to evaluate their precision, a hierarchical Bayesian approach is used. The study is motivated by a real SAE problem. We focus on estimation of the per‐farm average grape wine production in Tuscany, at subregional level, using the Farm Structure Survey data. Results from this real data application and those obtained by a model‐based simulation experiment show a satisfactory performance of the suggested SAE approach.