Abstract
Traditionally science has been concerned, in part, with the study of structure amongst variables. With the development of statistical concepts, such as the runs statistic, and the advent of time-series analysis, more recent attention has been turned to the study of structure amongst observations of a single variable. Within this context the notion of autocorrelation has received considerable treatment (see Bhat, 1974; Crowder, 1976; Silvey, 1961), with the special case of spatial autocorrelation receiving extensive consideration (see, for example, Cliff and Ord, 1981).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ahuja, N., and B. Schachter, 1983, Pattern Models. New York: Wiley.
Bhat, B., 1974, On the method of maximum-likelihood for dependent observations, Journal of the Royal Statistical Society B, Vol. 36: 48–53.
Cliff, A., and J. Ord, 1973, Spatial Autocorrelation. London: Pion.
Cliff, A., and J. Ord, 1981, Spatial Processes. London: Pion.
Costanzo, C., 1983, Statistical inference in geography: modern approaches spell better times ahead, The Professional Geographer, Vol. 35: 158–165.
Crowder, M., 1976, Maximum likelihood estimation for dependent observations, Journal of the Royal Statistical Society B, Vol. 38: 45–53.
Gaile, G., and J. Burt, 1980, Directional Statistics. Norwich, England: Geo Abstracts.
Getis, A., and B. Boots, 1978, Models of Spatial Processes. New York: Cambridge University Press.
Gould, P., 1970, Is statistix inferens the geographical name for a wild goose?, Economic Geography, Vol. 46 (supplement): 439–448.
Griffith, D., 1980, Towards a theory of spatial statistics, Geographical Analysis, Vol. 12: 325–339.
Griffith, D., 1984, Theory of spatial statistics, in Spatial Statistics and Models, edited by G. Gaile and C. Willmott. Boston: D. Reidel, pp. 3–15.
Griffith, D., 1987, Toward a theory of spatial statistics: another step forward, Geographical Analysis, Vol. 19: 69–82.
Haining, R., 1980, Spatial autocorrelation problems, in Geography and the Urban Environment: Progress in Research and Application, vol. 3, edited by D. Herbert and R. Johnston. New York: Wiley, pp. 1–44.
Haining, R., D. Griffith and R. Bennett, 1983, Simulating two-dimensional autocorrelated surfaces, Geographical Analysis, vol. 15: 247–255.
Haining, R., D. Griffith and R. Bennett, 1984, A statistical approach to the problem of missing spatial data using a first-order Markov model, The Professional Geographer, Vol. 36: 338–345.
Lindgren, B., 1976, Statistical Theory, 3rd ed. New York: MacMillan.
Schuenemeyer, J., 1984, Directional data analysis, in Spatial Statistics and Models, edited by G. Gaile and C. Willmott. Boston: D. Reidel, pp. 253–270.
Silvey, S., 1961, A note on maximum likelihood in the case of dependent random variables, Journal of the Royal Statistical Society B, Vol. 23: 444–452.
Smith, T., 1980, A central limit theorem for spatial samples, Geographical Analysis, Vol. 12: 299–324.
Steinnes, D., 1980., Aggregation, gerrymandering and spatial econometrics, Regional Science and Urban Economics, Vol. 10: 561–569.
Stephan, F., 1934, Sampling errors and the interpretation of social data ordered in time and space, Journal of the American Statistical Association, Vol. 29: 165–166.
Student, 1914, The elimination of spurious correlation due to position in time or space, Biometrika, Vol. 10: 179–180.
Summerfield, M., 1983, Populations, samples and statistical inference in geography, The Professional Geographer, Vol. 35: 143–149.
Upton, G., and B. Fingleton, 1985, Spatial Data Analysis by Example: Point Pattern and Quantitative Data, Vol. 1. New York: Wiley.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1988 Kluwer Academic Publishers, Dordrecht
About this chapter
Cite this chapter
Griffith, D.A. (1988). Introduction to Spatial Statistics and Data Handling. In: Advanced Spatial Statistics. Advanced Studies in Theoretical and Applied Econometrics, vol 12. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-2758-2_1
Download citation
DOI: https://doi.org/10.1007/978-94-009-2758-2_1
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-7739-2
Online ISBN: 978-94-009-2758-2
eBook Packages: Springer Book Archive