Change-Point Method Applied to the Detection of Temporal Variations in Seafloor Bacterial Mat Coverage
The paper is aimed at a methodological development of change-point detection, applicable in dentifying abrupt changes in temporal or spatial data sequences. In earlier papers we developed a method for detecting a change in the parameters of a discrete distribution, with the simultaneous estimation...
| Main Authors: | , , , , |
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| Format: | info:eu-repo/semantics/article |
| Language: | English |
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2017
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10835/4901 |
| _version_ | 1789406765184450560 |
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| author | López, Inmaculada Rodríguez, Carmelo Gámez Cámara, Manuel Angel Varga, M. Garay, J. |
| author_facet | López, Inmaculada Rodríguez, Carmelo Gámez Cámara, Manuel Angel Varga, M. Garay, J. |
| author_sort | López, Inmaculada |
| collection | DSpace |
| description | The paper is aimed at a methodological development of change-point detection, applicable in
dentifying abrupt changes in temporal or spatial data sequences. In earlier papers we developed a method for detecting a change in the parameters of a discrete distribution, with the simultaneous estimation of the (deterministic but unknown) distribution parameters before and after the change. In this paper we not only extend this method to the case of normal distributions, but also provide a new algorithm for the iterative refining of the estimation of the change-point, based on a "cleaning" of mixed-up parts of the samples. The appropriate size of reduced part of the sample is analytically calculated for the case of normal distributions. This "cleaning" is combined with our original change-point detection method. Our new algorithm is not only validated on artificial data, but also applied to a real environmental data set collected and analysed by other authors in a seafloor observatory. Our results detecting abrupt changes of bacterial mat coverage of a seafloor area are in harmony with the biological fluctuations and changes in the abiotic environment, analysed recently by other authors using a different method. We also provide a comparison with other existing change-point detection methods: a one-dimensional version of the gradient method widely used for edge detection, and a maximum type statistical method well-known in environmental studies. Although normality conditions of our method are rather restrictive, its application potential for environmental data sets is also demonstrated. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-4901 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2017 |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-49012023-04-12T19:39:49Z Change-Point Method Applied to the Detection of Temporal Variations in Seafloor Bacterial Mat Coverage López, Inmaculada Rodríguez, Carmelo Gámez Cámara, Manuel Angel Varga, M. Garay, J. Change-point detection Maximun likelihood method Multi-sensor seafloor observatories Bacterial mat coverage The paper is aimed at a methodological development of change-point detection, applicable in dentifying abrupt changes in temporal or spatial data sequences. In earlier papers we developed a method for detecting a change in the parameters of a discrete distribution, with the simultaneous estimation of the (deterministic but unknown) distribution parameters before and after the change. In this paper we not only extend this method to the case of normal distributions, but also provide a new algorithm for the iterative refining of the estimation of the change-point, based on a "cleaning" of mixed-up parts of the samples. The appropriate size of reduced part of the sample is analytically calculated for the case of normal distributions. This "cleaning" is combined with our original change-point detection method. Our new algorithm is not only validated on artificial data, but also applied to a real environmental data set collected and analysed by other authors in a seafloor observatory. Our results detecting abrupt changes of bacterial mat coverage of a seafloor area are in harmony with the biological fluctuations and changes in the abiotic environment, analysed recently by other authors using a different method. We also provide a comparison with other existing change-point detection methods: a one-dimensional version of the gradient method widely used for edge detection, and a maximum type statistical method well-known in environmental studies. Although normality conditions of our method are rather restrictive, its application potential for environmental data sets is also demonstrated. 2017-07-10T10:21:30Z 2017-07-10T10:21:30Z 2016 info:eu-repo/semantics/article Published in Journal of Environmental Informatics http://hdl.handle.net/10835/4901 doi:10.3808/jei.201500330 en http://www.jeionline.org/index.php?journal=mys&page=index Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
| spellingShingle | Change-point detection Maximun likelihood method Multi-sensor seafloor observatories Bacterial mat coverage López, Inmaculada Rodríguez, Carmelo Gámez Cámara, Manuel Angel Varga, M. Garay, J. Change-Point Method Applied to the Detection of Temporal Variations in Seafloor Bacterial Mat Coverage |
| title | Change-Point Method Applied to the Detection of Temporal Variations in Seafloor Bacterial Mat Coverage |
| title_full | Change-Point Method Applied to the Detection of Temporal Variations in Seafloor Bacterial Mat Coverage |
| title_fullStr | Change-Point Method Applied to the Detection of Temporal Variations in Seafloor Bacterial Mat Coverage |
| title_full_unstemmed | Change-Point Method Applied to the Detection of Temporal Variations in Seafloor Bacterial Mat Coverage |
| title_short | Change-Point Method Applied to the Detection of Temporal Variations in Seafloor Bacterial Mat Coverage |
| title_sort | change-point method applied to the detection of temporal variations in seafloor bacterial mat coverage |
| topic | Change-point detection Maximun likelihood method Multi-sensor seafloor observatories Bacterial mat coverage |
| url | http://hdl.handle.net/10835/4901 |
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