Spatial analysis from macroscale to microscale based on mutual information

• Autores: José Miguel Angulo Ibáñez , María Dolores Ruiz Medina , Ana Esther Madrid García
• Localización: XXX Congreso Nacional de Estadística e Investigación Operativa y de las IV Jornadas de Estadística Pública: actas, 2007, ISBN 978-84-690-7249-3
• Idioma: inglés
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• Resumen

  • Mutual information between a process of interest and an observed process is measured in terms of the wavelet transform. Blocks of wavelet coeffcients are considered to compute conditional entropy. Different block designs are formulated, with their performances depending on the local and global characteristics of both the interest and observed processes. The size of the blocks can also change with the scale, that is, from low-resolution (macro-scale) to high resolution (micro-scale) levels. In practice, the dispersion of the region of interest, the range of spatial dependence, and the local variability of the underlying models, including intensity of the observation noise, determine the optimal design of the blocks, as well as the thresholding rule for discrimination of useful information at different scales.