| Description: | [DMS Seminar] Dr. Anandamayee Majumdar (Center for Advanced Statistics and Economics, Soochow University, Suzhou) -- radients in Spatial Response Surfaces with Application to Urban Land Values |
| Date: | Monday, Apr 17, 2017 |
| Time: | 10:30 a.m. - 11:30 a.m. |
| Venue: | 108, Lecture Hall Complex |
| Details: | For point referenced spatial data, we often create explanatory models that introduce regression structure with error consisting of a spatial term and a white noise term. Here, we consider more flexible regression structures which allow spatially varying regression coefficients(Gelfand et al 2003 ). The resulting mean becomes a spatial response surface which is a linear combination of the components of the spatially varying coefficient vector. Of possible interest in this setting would be gradients associated with the coefficient surfaces as well as the mean surface. Gradients could be sought at arbitrary points and in arbitrary directions. Extending ideas developed in Banerjee et al (2003) we obtain a fully inferential approach within the Bayesian framework for examining such gradients. In particular, we can obtain posterior distributions for any such gradient, for the direction of maximal gradient and for the magnitude of the maximal gradient. The motivation for our work is the desire to examine urban land value gradients. There is considerable literature in the real estate community offering economic theory, modelling, and data analysis relating urban land values to distance from the city center. Here we focus on gradients to such surfaces. The flexibility of our approach allows for much richer insights into the behaviour of such gradients than previously available. We illustrate through fitting of a portion of Olcott’s classic Chicago land value data. |
| Calendar: | Seminar Calendar (entered by saugata.bandyopadhyay) |