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pro vyhledávání: '"Palm B"'
Autor:
Bumberger, J., Abbrent, M., Brinckmann, N., Hemmen, J., Kunkel, R., Lorenz, C., Lünenschloß, P., Palm, B., Schnicke, T., Schulz, C., van der Schaaf, H., Schäfer, D.
Addressing the challenges posed by climate change, biodiversity loss, and environmental pollution requires comprehensive monitoring and effective data management strategies that are applicable across various scales in environmental system science. Th
Externí odkaz:
http://arxiv.org/abs/2409.03351
Publikováno v:
Computational Statistics & Data Analysis, v. 171, July 2022
Two-dimensional (2-D) autoregressive moving average (ARMA) models are commonly applied to describe real-world image data, usually assuming Gaussian or symmetric noise. However, real-world data often present non-Gaussian signals, with asymmetrical dis
Externí odkaz:
http://arxiv.org/abs/2208.03615
Publikováno v:
IEEE Geoscience and Remote Sensing Letters, v. 19, 2020
The Rayleigh regression model was recently proposed for modeling amplitude values of synthetic aperture radar (SAR) image pixels. However, inferences from such model are based on the maximum likelihood estimators, which can be biased for small signal
Externí odkaz:
http://arxiv.org/abs/2208.03611
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing, v. 60, 2021
The presence of outliers (anomalous values) in synthetic aperture radar (SAR) data and the misspecification in statistical image models may result in inaccurate inferences. To avoid such issues, the Rayleigh regression model based on a robust estimat
Externí odkaz:
http://arxiv.org/abs/2208.00097
Publikováno v:
Digital Signal Processing, Volume 109, February 2021, 102911
This paper proposes the beta binomial autoregressive moving average model (BBARMA) for modeling quantized amplitude data and bounded count data. The BBARMA model estimates the conditional mean of a beta binomial distributed variable observed over the
Externí odkaz:
http://arxiv.org/abs/2208.00095
Publikováno v:
Communications in Statistics - Simulation and Computation, 2021
In this paper, we propose five prediction intervals for the beta autoregressive moving average model. This model is suitable for modeling and forecasting variables that assume values in the interval $(0,1)$. Two of the proposed prediction intervals a
Externí odkaz:
http://arxiv.org/abs/2207.11628
Autor:
Palm, B. G., Alves, D. I., Pettersson, M. I., Vu, V. T., Machado, R., Cintra, R. J., Bayer, F. M., Dammert, P., Hellsten, H.
Publikováno v:
Sensors 2020, 20(7)
This paper presents five different statistical methods for ground scene prediction (GSP) in wavelength-resolution synthetic aperture radar (SAR) images. The GSP image can be used as a reference image in a change detection algorithm yielding a high pr
Externí odkaz:
http://arxiv.org/abs/2207.11400
Publikováno v:
IEEE Geoscience and Remote Sensing Letters, v. 16, n. 10, pp. 1660-1664, 2019
This letter proposes a regression model for nonnegative signals. The proposed regression estimates the mean of Rayleigh distributed signals by a structure which includes a set of regressors and a link function. For the proposed model, we present: (i)
Externí odkaz:
http://arxiv.org/abs/2207.11397
Autor:
Palm, B. G., Alves, D. I., Vu, V. T., Pettersson, M. I., Bayer, F. M., Cintra, R. J., Machado, R., Dammert, P., Hellsten, H.
Publikováno v:
Proceedings Volume 10789, Image and Signal Processing for Remote Sensing XXIV; 1078916 (2018)
Change detection is an important synthetic aperture radar (SAR) application, usually used to detect changes on the ground scene measurements in different moments in time. Traditionally, change detection algorithm (CDA) is mainly designed for two synt
Externí odkaz:
http://arxiv.org/abs/2206.02278
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