Robust estimation for spatial autoregressive processes based on bounded innovation propagation representations
| Autor: | Grisel Maribel Britos, Silvia Ojeda |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Statistics and Probability
IMAGE PROCESSING Computer science Estadística y Probabilidad Matemáticas Monte Carlo method Image processing Context (language use) ROBUST ESTIMATORS 01 natural sciences AR-2D MODELS 010104 statistics & probability 0502 economics and business 0101 mathematics Spatial analysis 050205 econometrics Noise (signal processing) 05 social sciences Estimator SPACIAL MODELS Computational Mathematics Autoregressive model Outlier Statistics Probability and Uncertainty Algorithm CIENCIAS NATURALES Y EXACTAS |
| Popis: | Robust methods have been a successful approach for dealing with contamination and noise in the context of spatial statistics and, in particular, in image processing. In this paper, we introduce a new robust method for spatial autoregressive models. Our method, called BMM-2D, relies on representing a two-dimensional autoregressive process with an auxiliary model to attenuate the effect of contamination (outliers). We compare the performance of our method with existing robust estimators and the least squares estimator via a comprehensive Monte Carlo simulation study, which considers different levels of replacement contamination and window sizes. The results show that the new estimator is superior to the other estimators, both in accuracy and precision. An application to image filtering highlights the findings and illustrates how the estimator works in practical applications. Fil: Britos, Grisel Maribel. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina Fil: Ojeda, Silvia María. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina |
| Databáze: | OpenAIRE |
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