A Quantile Regression Approach to Evaluate Factors Influencing Residential Indoor Radon Concentration

被引:15
作者
Borgoni, Riccardo [1 ]
机构
[1] Univ Milano Bicocca, Dept Stat, I-20121 Milan, Italy
关键词
Building factors; Spatial quantile additive autoregression; Spatial lag; PREDICTION; URANIUM;
D O I
10.1007/s10666-011-9249-3
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Indoor radon concentrations depend on building characteristics such as building materials, ventilation and water supply. In this paper, a quantile regression approach is proposed to evaluate the effect of some buildings factors potentially influencing indoor radon concentration. Many of the considered factors, such as soil connection, age of construction and being a single family building, are found to have a statistically significant effect; however, this is far from being constant across the entire support of indoor radon concentration. A potential impact due to geological and geo-physical reasons is also found using the altitude of building locations as a surrogate variable. In addition, a clear local spatial effect is detected by a spatial autoregression approach.
引用
收藏
页码:239 / 250
页数:12
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