Spearman's rank correlation coefficient is a nonparametric (distribution-free) rank statistic
proposed by Charles Spearman as a measure of the strength of an association between two …

Applications of machine-learning-based approaches in the geosciences have witnessed a
substantial increase over the past few years. Here we present an approach that accounts for …

Background: West Nile virus (WNV) is the leading cause of mosquito-borne disease in
humans in the United States. Since the introduction of the disease in 1999, incidence levels …

Mass real estate valuation is a multidimensional and complex matter because it depends on
many constant and time-varying factors. It is desirable to have high level of model …

This paper investigates the role of spatial dependence, spatial heterogeneity and spatial
scale in principal component analysis for geographically distributed data. It considers spatial …

Using panel data from Nepal Living Standard Surveys (NLSSs) from 2003 and 2010, this
study investigates the impact of climate change on rice production in Nepal. Specifically, we …

Exploration of geothermal resources involves analysis and management of a large number
of uncertainties, which makes investment and operations decisions challenging. Remote …

Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical
foundations and guides practical implementation of the Moran eigenvector spatial filtering …

This study develops a spatially varying coefficient model by extending the random effects
eigenvector spatial filtering model. The developed model has the following properties: its …

Eigenvector spatial filtering (ESF) is becoming a popular way to address spatial
dependence. Recently, a random effects specification of ESF (RE-ESF) is receiving …