Regression analysis of spatial data

Regression analysis of spatial data.

Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative anal...

Spatial Regression in the Presence of Misaligned data

In this paper, four approaches are presented to the problem of fitting a linear regression model in the presence of spatially misaligned data. These approaches are plug-in method‎, ‎simulation‎, ‎regression calibration and maximum likelihood‎. In the first two approaches‎, ‎with modeling the correlation between the explanatory variable, prediction of explanatory variable is determined at sites...

Spatial Regression Models for Areal Data Analysis

The primary models of interest for areal data analysis are regression models. In the same way that geo-regression models were used to study relations among continuous-data attributes of selected point locations (such as the California rainfall example), the present spatial regression models are designed to study relations among attributes of areal units (such as the English Mortality example in...

Spatial Correlation Testing for Errors in Panel Data Regression Model

To investigate the spatial error correlation in panel regression models, various statistical hypothesizes and testings have been proposed. This paper, within introduction to spatial panel data regression model, existence of spatial error correlation and random effects is investigated by a joint Lagrange Multiplier test, which simultaneously tests their existence. For this purpose, joint Lagrang...

Bayesian Prediction in Spatial Data Analysis