Portfolio theory shows that diversification can enhance the riskreturn trade-off. This study uses the absolute location of commercial real estate property along with spatial statistics to address the inherent problem of determining geographical diversification based upon a set of economic and property-specific attributes, some of which are unobservable or must be proxied with noise. We find tha...

A Content Based Image Retrieval (CBIR) system retrieves relevant images from an image database. Over the years, several methods have been proposed to extract these features. Previous researches show that the effectiveness of a CBIR system increases when spatial relationship of colours is considered. In this paper we propose using the Looseness parameter from geostat, a branch of statistics whic...

We consider the problem of design of a network of observation locations in a spatial domain that will be used to interpolate a spatial field. We compare design strategies based on simultaneous simulated annealing [1, 3] and sequential point selection algorithms [2] using criteria such as minimum estimation variance (MEV), maximum conditional variance (MCV) [2] and maximum entropy [5, 6]. Design...

From the abacus to the adding machine to the supercomputer, for centuries humans have used aids to enable mathematical computations. As the mathematical tabulations grew in complexity, so did the ‘machines’ that enabled more complex calculations. This in turn presented the problem of implementing beautifully written formulas in a form a computer ‘aid’ could understand. Today statistics specific...

Kulldorff’s spatial scan statistic and the software implementation (SaTScan) are widely used for the detection and evaluation of geographic clusters, particularly within the health care community. Unfortunately, the computational time of the scan statistic depends on a wide variety of variables, and, depending on the chosen parameter settings and operations, the computational time can be on the...

We summarize and discuss the current state of spatial point process theory and directions for future research, making an analogy with generalized linear models and random effect models, and illustrating the theory with various examples of applications. In particular, we consider Poisson, Gibbs, and Cox process models, diagnostic tools and model checking, Markov chain Monte Carlo algorithms, com...

The spatial scan statistic is one of the main epidemiological tools to test for the presence of disease clusters in a geographical region. While the statistical significance of the most likely cluster is correctly assessed using the model assumptions, secondary clusters tend to have conservatively high P-values. In this paper, we propose a sequential version of the spatial scan statistic to adj...