Statistics for Spatial Data
Statistics for Spatial Data
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DOI：
10.1080/00401706.1993.10485328
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发表时间：
1993-08
期刊：
影响因子：
2.5
通讯作者：
R. D. Veaux
中科院分区：
文献类型：
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作者：
R. D. Veaux
1989年春天，我在普林斯顿大学教授一门空间统计学研究生课程。这些学生来自土木工程、地质和电气工程等领域，从大四的本科生到教职员工都有。在课程开始之前，我记得我给诺埃尔·克雷西打过电话，征求他们的建议、同情，最重要的是，我还向他们推荐了这门课程的教科书。我看过《克利夫与奥德》(1981)、《乔内尔与惠布雷茨》(1978)、《厄普顿与芬格顿》(1985)以及《雷普利》(1981)。没有一个和我想要的一模一样。诺埃尔的回答很快就来了：“用克雷西(1991)”，他开玩笑说。事实上，我希望我能做到这一点，我期待着再次教授这门课程，因为它已经结束了！空间统计学是一个巨大的领域，不幸的是，它不是大多数专业统计学家标准培训的一部分。尽管大多数用户仍然是地球科学家，但空间统计的工业用途继续增长。这本书是为专业统计学家和其他研究人员提供该领域的全面介绍的重要一步。对于Spatiul Dnta来说，学习是一项令人印象深刻的成就和真正的环法自行车赛。在900多页中，它涵盖了空间统计的主题领域，既有广泛的广度，也有实质性的深度。这本参考书目长达70页，表明了自始至终的高水平学术水平。导言的第一句话是：“这本书的目的是向科学家和工程师介绍空间数据的统计学。”当然，这个目标已经很好地实现了。过了一会儿，他说：“这本书试图将这部文学作品加以扩展、更正和统一。那些看似互不相连的主题领域的聚集，可以被改造成一种分析空间数据的连贯方法。我想我再也写不出比这本书更准确的摘要了。
In the spring of 1989, I taught a graduate course in spatial statistics at Princeton. The students came from civil engineering, geology, and electrical engineering, among other fields, and ranged in level from senior undergraduates to faculty. Before the course started, I remember calling Noel Cressie to get advice, sympathy, and, most importantly, a textbook recommendation for the course. I had looked at Cliff and Ord (1981), Journel and Huijbregts (1978), Upton and Fingleton (1985), and Ripley (1981). None were exactly what I was looking for. Noel’s reply came quickly:“Use Cressie (1991)” he joked. Indeed, I wish that I had been able to, and I look forward to teaching the course again now that it is out!Spatial statistics is an enormous field that is not unfortunately part of the standard training of most professional statisticians. Although the majority of the users are still geoscientists, the industrial uses of spatial statistics continue to grow. This book is an important step in providing professional statisticians and other researchers a comprehensive introduction to the area. Stutistics for Spatiul Dnta is an impressive accomplishment and a true tour de force. In its more than 900 pages, it covers the subject area of spatial statistics in sweeping breadth as well as substantive depth. The bibliography spans 70 pages and is indicative of the high level of scholarship throughout. The first sentence of the introduction states:“The purpose of the book is to present Statistics for spatial data to scientists and engineers.” Certainly this goal is well met. A bit later, he states,“This book attempts to take that literature and extend it, correct it, and unify it. What appears to be a gathering of unconnected subject areas can be annealed into a cohesive approach to the analysis of spatial data.” I do not think I could have written a more precise summary of the book.