K.C.S.Pillai Memorial Lecture

Spatial Data Analysis

B.L.S. Prakasa Rao
Indian Statistical Institute

Start Date and Time: Mon, 22 Apr 1996, 4:30 PM

End Date and Time: Mon, 22 Apr 1996, 5:30 PM

Venue: LAEB Room 1268


In order to study the relationship between one variable and another variable, classical statistical methods range from scatter plot techniques for visual exploration of data to regression analysis and more sophisticated techniques. Regression techniques might include some explanatory variables or covariates other than the two variables under consideration. However one factor which may not be incorporated in the standard regression analysis is the spatial configuration of the observational units. For instance, in the study of relationships between voting pattern or support for a political party and the level of income, the party support and per capita income in one region may be related to those in the neighboring constituencies in addition to the relationship with each other within the region. In this talk which is of introductory nature, we will briefly describe four types of spatial data: point patterns, spatially continuous data, aerial data and spatial interaction data. Some methods of statistical analysis for such data will be presented. Application of methods of nonparametric inference and statistical analysis of random fields to such data will be discussed.


  1. Statistical analysis of spatial point patterns, Diggle (1983)
  2. Effective observation of random fields, Nather (1985)
  3. Spatial statistics and imaging (Ed., Possolo)
  4. Statistics for spatial data, Cressie (1993)
  5. Interactive spatial data analysis, Barley and Gatrell (1995) 

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