A Geostatistical Heterogeneity Metric for Spatial Feature Engineering

Geostatistical Analysis of Spatial Data

First, geostatistics provides descriptive tools such as semivariograms to characterize the spatial pattern of continuous and categorical soil attributes. Various interpolation (kriging) techniques capitalize on the spatial correlation between observations to predict attribute values at unsampled locations using information related to one or several attributes. An important contribution of geost...

A Geostatistical Approach for Describing Spatial Pattern in Stream Networks

Spatial heterogeneity of parasite co-infection: Determinants and geostatistical prediction at regional scales

Multiple parasite infections are widespread in the developing world and understanding their geographical distribution is important for spatial targeting of differing intervention packages. We investigated the spatial epidemiology of mono- and co-infection with helminth parasites in East Africa and developed a geostatistical model to predict infection risk. The data used for the analysis were ta...

A Geostatistical Framework for Area-to-Point Spatial Interpolation

The spatial prediction of point values from areal data of the same attribute is addressed within the general geostatistical framework of change of support; the term support refers to the domain informed by each datum or unknown value. It is demonstrated that the proposed geostatistical framework can explicitly and consistently account for the support differences between the available areal data...

Feature Engineering in Persian Dependency Parser

Dependency parser is one of the most important fundamental tools in the natural language processing, which extracts structure of sentences and determines the relations between words based on the dependency grammar. The dependency parser is proper for free order languages, such as Persian. In this paper, data-driven dependency parser has been developed with the help of phrase-structure parser fo...