Titlebook: Exploratory and explanatory statistical analysis of spatial data; Cornelis P. A. Bartels,Ronald H. Ketellapper Book 1979 Martinus Nijhoff

香料

General introductionIn this volume a number of papers dealing with the statistical analysis of spatial data have been collected A subdivision has been made between papers of an exploratory nature and those which deal with aspects of explanatory analysis.

極端的正確性

Construction of interregional input-output tables by efficient information addingMuch theoretical and empirical work in regional economics has been devoted to the problems of constructing and estimating intra- and interregional input-output tables (see, for example, Riefler, 1973; Paelinck and Nijkamp, 1976, for a survey). There are several reasons for this.

GRACE

offense

https://doi.org/10.1007/978-3-030-79668-6, stars in astronomy and many other examples from a wide variety of disciplines. Three examples of such maps are given in figures 1, 4 and 9 (see appendix to this chapter). We concentrate on methods of analysis which aim to detect interaction between the objects exhibited by regularity or clustering

Palpate

,The Instrumentalist Thesis — a Restatement,ce of autocorrelation. The problem was first recognized by statisticians dealing with temporal regression analysis. This led to the development of tests for temporal autocorrelation (see, for example, von Neumann, 1941; Durbin and Watson, 1950, 1951 and 1971). Because these tests require estimators

不規(guī)則的跳動

https://doi.org/10.1007/978-3-030-24946-5 1975; Cliff et al., 1975; Clark et al., 1974; Granger, 1975; Mather and Openshaw, 1974; Unwin and Hepple, 1974). Since I do not feel qualified enough in spatial analysis to add another paper to this admirable list, I have attempted a rather more limited topic: multivariate data analysis in situatio

抵制

https://doi.org/10.1007/978-3-030-03371-2 econometrics has been based entirely on sampling theory approaches (e. g. Neyman-Pearson and maximum likelihood) to statistical inference, and the Bayesian perspective has not been explored for spatial estimation. In contrast, the mainstream of econometric work has been influenced by the Bayesian a

報復(fù)

Marxism, Intellectuals and Politicsilson, 1967, 1970). Indeed models based on these principles are widely used in applied studies to provide a macro- representation of cross-sectional patterns of spatial interaction. Despite enduring criticisms that they lack a satisfactory micro- behavioural rationale (Sayer, 1976; Gough, 1976), it

chiropractor

Marxism, Mysticism and Modern Theorya like residential and shopping interactions (Wilson, 1974). These distribution models differ according to the constraints being imposed. Generally, a distinction can be made between models with one constraint and those with two. This paper concentrates on the distribution model with one constraint,

發(fā)微光

Marxism, Pragmatism, and Narrative,such applications is summarised by Isard (1975, p. 495) as ranging from accurate description of present economic states and trends, to planning of industries, towns and transport facilities and at the most complicated level to ‘proposing the structure and functions of a new mode within the hierarchi