Robust estimators and bootstrap confidence intervals applied to tourism spending
Robust estimators and bootstrap confidence intervals applied to tourism spending
复制标题
适用于旅游支出的稳健估计量和引导置信区间
DOI：
10.1016/j.tourman.2004.06.016
复制
发表时间：
2006
影响因子：
12.7
通讯作者：
Pedro Cortiñas Vázquez
中科院分区：
文献类型：
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作者：
A. P. Pol;M. Pascual;Pedro Cortiñas Vázquez
过去几年对旅游业重要方面进行的统计研究表明，旅游产品的供需情况有所上升。本研究侧重于评估旅游支出的一个基本变量：每位游客的平均每日支出的各种方法。在分析此变量时，使Average Location参数无效的极值并不少见。偏斜值的存在和分布的不对称性证明了使用替代方法进行参数估计是合理的。利用2001年在巴利阿里群岛进行的旅游支出调查收集的数据，本研究提出了不同稳健位置估计器的结果，特别强调Huber和一步M估计器，并计算了可信区间。此外，结果是通过使用一种称为Bootstrap估计的重新采样方法获得的。
Statistical research carried out over the past few years evaluating important aspects of tourism has shown that supply and demand for tourism products have risen. This study focuses on various methods of evaluating a fundamental variable of tourist expenditure: average daily expenses per tourist. When analysing this variable, extreme values that invalidate the average location parameter are not uncommon. The presence of skewed values and the asymmetry of distribution justify using alternative methods for parameter estimation. Using data collected from the tourist expenditure survey taken in the Balearic Islands in 2001, this study presents results obtained from different robust location estimators, placing special emphasis on Huber and one-step's M-estimators, accompanied by calculating confidence intervals. Additionally, results were obtained by using a resampling method called the bootstrap estimation.