Local likelihood disease clustering: development and evaluation

Local Likelihood and Local Partial Likelihood in Hazard Regression

Local Likelihood SiZer Map

The SiZer Map, proposed by Chaudhuri and Marron (1999), is a statistical tool for finding which features in noisy data are strong enough to be distinguished from background noise. In this paper, we propose the local likelihood SiZer map. Some simulation examples illustrate that the newly proposed SiZer map is more efficient in distinguishing features than the original one, because of the infere...

Power evaluation of disease clustering tests

BACKGROUND: Many different test statistics have been proposed to test for spatial clustering. Some of these statistics have been widely used in various applications. In this paper, we use an existing collection of 1,220,000 simulated benchmark data, generated under 51 different clustering models, to compare the statistical power of several disease clustering tests. These tests are Besag-Newell'...

Local Maximum Likelihood Multiuser Detection

It is well-known that the optimum multiuser detector achieves the global maximum likelihood (GML) detection in the entire set of hypotheses and several other iterative detectors such as the SAGE detector achieve the local maximum likelihood (LML) detection in the smallest neighborhood. In this paper, we generalize the local maximum likelihood detection into any size of neighborhood. The charact...

Development and Evaluation of Clustering Techniques for Finding People

Typically in a large organisation much expertise and knowledge is held informally within employees’ own memories. When employees leave an organisation many documented links that go through that person are broken and no mechanism is usually available to overcome these broken links. This matchmaking problem is related to the problem of finding potential work partners in a large and distributed or...