Outlier detection concerns discovering some unusual data whose behavior is exceptional compared to other data. In contrast to non-spatial outliers which only consider non-spatial attributes, spatial outliers are defined to be those sites which are very different from its neighbors defined in terms of spatial attributes, i.e., locations. In this paper, we propose a local trimmed mean approach to...

background: this study was conducted to detect clusters of pulmonary tb cases in hamadan province, west of iran. methods: all patients with pulmonary tuberculosis recorded in the surveillance system from 2005 to 2013 were studied. the spatial scan statistic was used to detect significant clusters in status of unadjusted and adjusted for age, sex and location residence variables. results: cluste...

Motivated by applications to goodness of fit degenerate U-statistics testing, the Jackknife empirical likelihood approach for U-statistics is generalized to degenerate U-statistics. The proposed empirical likelihood based goodness of fit tests are asymptotically distribution free. The asymptotic theory for testing shift of location, spatial depth testing for central symmetry, Cramér-von Mises t...

BACKGROUND The purpose of this study is to examine the spatial and population (e.g., socio-economic) characteristics of low birthweight using two different cluster estimation techniques. We compared the results of Kulldorff's Spatial Scan Statistic with the results of Rushton's Spatial filtering technique across increasing sizes of spatial filters (circle). We were able to demonstrate that vary...

The creation of a spatial weights matrix by a procedure called AMOEBA, A Multidirectional Optimum Ecotope-Based Algorithm, is dependent on the use of a local spatial autocorrelation statistic. The result is (1) a vector that identifies those spatial units that are related and unrelated to contiguous spatial units and (2) a matrix of weights whose values are a function of the relationship of the...

For a vector y ∈ Rn and a model subspace X ⊂ Rn, the residual configuration statistic is what remains of y when translations in the model space and scalar multiplication are ignored. The configuration statistic for a linear Gaussian model has a distribution that depends only on variance-component ratios, or similar ratio parameters in the covariance function of a spatial model. The marginal lik...

OBJECTIVE The use of spatially based methods and algorithms in epidemiology and surveillance presents privacy challenges for researchers and public health agencies. We describe a novel method for anonymizing individuals in public health data sets by transposing their spatial locations through a process informed by the underlying population density. Further, we measure the impact of the skew on ...

With the increasing availability of spatial data in many applications, spatial clustering and outlier detection has received a lot of attention in the database and data mining community. As a very prominent method, the spatial scan statistic finds a region that deviates (most) significantly from the entire dataset. In this paper, we introduce the novel problem of mining regional outliers in spa...