This research note documents estimation procedures and results for an empirical investigation of the performance of the recently developed spatial, heteroskedasticity and autocorrelation consistent (HAC) covariance estimator calibrated with different kernel bandwidths. The empirical example is concerned with a hedonic price model for residential property values. The first bandwidth approach var...

Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. No...

[1] As analogs for aquifers, outcrops of sedimentary deposits allow sedimentary units to be mapped, permeability to be measured with high resolution, and sedimentary architecture to be related to the univariate and spatial bivariate statistics of permeability. Sedimentary deposits typically can be organized into hierarchies of unit types and associated permeability modes. The types of units and...

[1] Cross-stratified deposits can give rise to a hierarchy of permeability modes, across scales, corresponding to a hierarchy of sedimentary unit types. The shape of the sample semivariogram for permeability can be largely controlled by the shape of the crosstransition probabilities of unit types having the greatest contrast in permeability. The shape of those cross-transition probabilities can...

The empirical semivariogram of residuals from a regression model with stationary errors may be used to estimate the covariance structure of the underlying process. For prediction (kriging) the bias of the semivariogram estimate induced by using residuals instead of errors has only a minor eeect because the bias is small for small lags. However, for estimating the variance of estimated regressio...

abstract- the information on the spatial properties of soil is vital to improve soil management and to increase the crop productivity. geostatistical analysis technique is one of the most important methods for determining the spatial properties of soil. the aim of this study was to investigate spatial variability of soil chemical and physical attributes for field management in eastern shiraz, i...

Lecoustre, R., Fargette, D., Fauquet, C., and de Reffye, P. 1989. Analysis and mapping of the spatial spread of African cassava mosaic virus using geostatistics and the kriging technique. Phytopathology 79: 913-920. Theories of regionalized variables and kriging were used to assess the incidence along the wind-exposed southwest field borders, disease spatial pattern of African cassava mosaic vi...