Introduction

Daniel A. Griffith
Additional contact information
Daniel A. Griffith: Syracuse University

Chapter 1 in Spatial Autocorrelation and Spatial Filtering, 2003, pp 1-32 from Springer

Abstract: Abstract At least since the dawn of civilization data have been analyzed as numerical figures to support a decision or to understanding a part of reality. Until the advent of the modern computer, data had to be collected manually and necessary calculations had to be done by hand, often restricting the volume of data analyzed to a very modest size. The computer has enabled the collection of vast amounts of data with greater ease and the performance of necessary data analysis calculations with far fewer mistakes and with considerably greater speed. With this transformation the new restriction to the volume of data analyzed became one based upon computer memory (RAM and ROM) and the speed of input and output devices. Initially this restriction resulted in two classes of computer: standard ones used by most scientists, mainframes and desktop PCs, and then supercomputers housed in a handful of regional centers. In recent years standard desktop PCs have become as powerful as earlier supercomputers, with differences between the two1.

Keywords: Lyme Disease; Areal Unit; Poisson Random Variable; Positive Spatial Autocorrelation; Scientific Visualization (search for similar items in EconPapers)
Date: 2003
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:adspcp:978-3-540-24806-4_1

Ordering information: This item can be ordered from
http://www.springer.com/9783540248064

DOI: 10.1007/978-3-540-24806-4_1

Access Statistics for this chapter

More chapters in Advances in Spatial Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().