Advanced Spatial Statistics: Special Topics In The Exploration Of Quantitative Spatial Data Series (advanced Studies In Theoretical And Applied Econometrics)
by Daniel A. Griffith /
2011 / English / PDF
10.3 MB Download
In recent years there has been a growing interest in and concern
for the development of a sound spatial statistical body of theory.
This work has been undertaken by geographers, statisticians,
regional scientists, econometricians, and others (e. g. ,
sociologists). It has led to the publication of a number of books,
including Cliff and Ord's Spatial Processes (1981), Bartlett's The
Statistical Analysis of Spatial Pattern (1975), Ripley's Spatial
Statistics (1981), Paelinck and Klaassen's Spatial Economet~ics
(1979), Ahuja and Schachter's Pattern Models (1983), and Upton and
Fingleton's Spatial Data Analysis by Example (1985). The first of
these books presents a useful introduction to the topic of spatial
autocorrelation, focusing on autocorrelation indices and their
sampling distributions. The second of these books is quite brief,
but nevertheless furnishes an eloquent introduction to the rela
tionship between spatial autoregressive and two-dimensional
spectral models. Ripley's book virtually ignores autoregressive and
trend surface modelling, and focuses almost solely on point pattern
analysis. Paelinck and Klaassen's book closely follows an
econometric textbook format, and as a result overlooks much of the
important material necessary for successful spatial data analy
sis. It almost exclusively addresses distance and gravity models,
with some treatment of autoregressive modelling. Pattern Models
supplements Cliff and Ord's book, which in combination provide a
good introduction to spatial data analysis. Its basic limitation is
a preoccupation with the geometry of planar patterns, and hence is
very narrow in scope.
In recent years there has been a growing interest in and concern
for the development of a sound spatial statistical body of theory.
This work has been undertaken by geographers, statisticians,
regional scientists, econometricians, and others (e. g. ,
sociologists). It has led to the publication of a number of books,
including Cliff and Ord's Spatial Processes (1981), Bartlett's The
Statistical Analysis of Spatial Pattern (1975), Ripley's Spatial
Statistics (1981), Paelinck and Klaassen's Spatial Economet~ics
(1979), Ahuja and Schachter's Pattern Models (1983), and Upton and
Fingleton's Spatial Data Analysis by Example (1985). The first of
these books presents a useful introduction to the topic of spatial
autocorrelation, focusing on autocorrelation indices and their
sampling distributions. The second of these books is quite brief,
but nevertheless furnishes an eloquent introduction to the rela
tionship between spatial autoregressive and two-dimensional
spectral models. Ripley's book virtually ignores autoregressive and
trend surface modelling, and focuses almost solely on point pattern
analysis. Paelinck and Klaassen's book closely follows an
econometric textbook format, and as a result overlooks much of the
important material necessary for successful spatial data analy
sis. It almost exclusively addresses distance and gravity models,
with some treatment of autoregressive modelling. Pattern Models
supplements Cliff and Ord's book, which in combination provide a
good introduction to spatial data analysis. Its basic limitation is
a preoccupation with the geometry of planar patterns, and hence is
very narrow in scope.
