Hierarchical Clustering with Spatial Constraints and Standardized Incidence Ratio in Tuberculosis Data
| Autor: | Ramón Gutiérrez Sánchez, Dalila Camêlo Aguiar, Edwirde Luiz Silva Camêlo |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
spatial constraints
measure of risk General Mathematics Feature vector Contiguity 01 natural sciences 010104 statistics & probability 03 medical and health sciences Matrix (mathematics) Statistics Computer Science (miscellaneous) Tuberculosis Point (geometry) State of Paraíba Brazil 0101 mathematics Cluster analysis ward-like algorithm Engineering (miscellaneous) 030304 developmental biology Mathematics 0303 health sciences lcsh:Mathematics Perspective (graphical) Ward-like algorithm lcsh:QA1-939 Hierarchical clustering Alpha (programming language) Measure of risk ComputingMethodologies_PATTERNRECOGNITION Spatial constraints |
| Zdroj: | Mathematics Volume 8 Issue 9 Mathematics, Vol 8, Iss 1478, p 1478 (2020) Digibug: Repositorio Institucional de la Universidad de Granada Universidad de Granada (UGR) Digibug. Repositorio Institucional de la Universidad de Granada instname |
| Popis: | In this paper, we propose presenting a solution based on socio-epidemiological variables of tuberculosis, considering a clustering with spatial/geographical constraints and, determine a value of alpha that increases spatial contiguity without significantly deteriorating the quality of the solution based on the variables of interest, i.e. those of the feature space. For the application of Ward&rsquo s hierarchical clustering method, two dissimilarity matrices were calculated, the first provides the dissimilarities in the feature space calculated from the socio-epidemiological variables D0 and the second provides the dissimilarities in the calculated constraints space from the geographical distances D1, together with an &alpha mixing parameter and the non-uniform weight w assigned to the calculation of the dissimilarity matrix defined by the standardized incidence ratio (SIR) of TB and that contributed significantly to the increase in clarity, both from a spatial and socio-epidemiological point of view. The method is shown to be feasible in epidemiological studies in the joint understanding of factors of different dimensions, aggregated from a spatial perspective. It is analysis tool that allows making a better understanding of the socio-epidemiological reality of the municipality. |
| Databáze: | OpenAIRE |
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