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- James P. LeSage
- 1999

A Bayesian probit model with individual effects that exhibit spatial dependencies is set forth. Since probit models are often used to explain variation in individual choices, these models may well exhibit spatial interaction effects due to the varying spatial location of the decision makers. That is, individuals located at similar points in space may tend… (More)

- Franck-Emmanuel Roux, Kader Boulanouar, Jean-Albert Lotterie, Mehdi Mejdoubi, James P LeSage, Isabelle Berry
- Neurosurgery
- 2003

OBJECTIVE
The aim of this study was to analyze the usefulness of preoperative language functional magnetic resonance imaging (fMRI), by correlating fMRI data with intraoperative cortical stimulation results for patients with brain tumors.
METHODS
Naming and verb generation tasks were used, separately or in combination, for 14 right-handed patients with… (More)

- James P. LeSage
- 1999

Toolboxes are the name given by the MathWorks to related sets of MATLAB functions aimed at solving a particular class of problems. Toolboxes of functions useful in signal processing, optimization, statistics, finance and a host of other areas are available from the MathWorks as add-ons to the standard MATLAB software distribution. I use the term Spatial… (More)

- Nicolas Debarsy, Cem Ertur, +4 authors James P. LeSage
- 2010

There is a great deal of literature regarding the asymptotic properties of various approaches to estimating simultaneous space-time panel models, but little attention has been paid to how the model estimates should be interpreted. The motivation for use of space-time panel models is that they can provide us with information not available from… (More)

- R. Kelley Pace, James P. LeSage
- Encyclopedia of GIS
- 2008

- R. Kelley Pace, James P. LeSage
- Computational Statistics & Data Analysis
- 2004

- James P. LeSage
- 2003

We introduce the matrix exponential as a way of modelling spatially dependent data. The matrix exponential spatial specification simplifies the loglikelihood allowing a closed form solution to the problem of maximum likelihood estimation, and greatly simplifies Bayesian estimation of the model. The matrix exponential spatial specification can produce… (More)

- James P. LeSage
- 1999

A Bayesian treatment of locally linear regression methods introduced in McMillen (1996) and labeled geographically weighted regressions (GWR) in Brunsdon, Fotheringham and Charlton (1996) is set forth in this paper. GWR uses distance-decay-weighted sub-samples of the data to produce locally linear estimates for every point in space. While the use of locally… (More)

- Geoffrey J. D. Hewings, Cem Ertur, Julie Le Gallo, James P. LeSage
- 2003

Numerous studies have pointed to the econometric problems introduced by heterogeneity in cross-sectional data samples used to explore convergence suggested by neo-classical growth models. We introduce a local concept of convergence along with a Bayesian locally linear spatial estimation method to address these problems. The method allows global and local… (More)