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The use of univariate Bayes regression models for spatial smoothing

R. Nishii, T. Yanagimoto, and S. Kusanobu. Computational Statistics & Data Analysis, 24 (3): 321--336 (May 12, 1997)

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Contextual Image Classification Based on Spatial Boosting.R. Nishii. IGARSS, page 2137-2140. IEEE, (2006)Non-linear regression models to identify functional forms of deforestation.S. Tanaka, and R. Nishii. IGARSS (4), page 49-52. IEEE, (2008)More precise tables of Srivastava-Chopra balanced optimal 2m fractional factorial designs of resolution V, m<=6R. Nishii, and T. Shirakura. Journal of Statistical Planning and Inference, (1986)Supervised image classification based on adaboost with contextual weak classifiers.R. Nishii, and S. Eguchi. IGARSS, page 1467-1470. IEEE, (2004)Contextual image segmentation based on AdaBoost and Markov random fields.R. Nishii. IGARSS, page 3507-3509. IEEE, (2003)Analytical estimation of the convergence point of populations.N. Murata, R. Nishii, H. Takagi, and Y. Pei. CEC, page 2619-2624. IEEE, (2015)Two Stage Estimation Procedure of Non-Linear Regression Functions for Spatially-Dependent Data.R. Nishii, and S. Tanaka. IGARSS, page 1520-1523. IEEE, (2020)Nonlinear Bayesian unmixing of geospatial data based on GIBBS sampling.R. Nishii, P. Qin, and D. Uchi. IGARSS, page 3104-3107. IEEE, (2013)Contextual Unmixing of Geospatial Data based on Gaussian Mixture Models and Markov Random Fields.R. Nishii, Y. Sawamura, A. Nakamoto, and S. Kawaguchi. IGARSS (4), page 77-80. IEEE, (2008)Hyperspectral Image Classification by AdaBoost with Decision Stumps Based on Composed Feature Variables.S. Kawaguchi, and R. Nishii. IGARSS, page 936-939. IEEE, (2006)

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The use of univariate Bayes regression models for spatial smoothing

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML The use of univariate Bayes regression models for spatial smoothing

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The use of univariate Bayes regression models for spatial smoothing