Spatial Signal Detection Using Continuous Shrinkage Priors

Jhuang, An -Ting; Fuentes, Montserrat; Jones, Jacob L.; Esteves, Giovanni; Fancher, Chris M.; Furman, Marschall; Reich, Brian J.

doi:10.1080/00401706.2018.1546622

Title: Spatial Signal Detection Using Continuous Shrinkage Priors

Journal Article · Fri Mar 22 00:00:00 EDT 2019 · Technometrics

DOI:https://doi.org/10.1080/00401706.2018.1546622· OSTI ID:1504020

Jhuang, An -Ting ^[1]; Fuentes, Montserrat ^[2]; Jones, Jacob L. ^[1]; Esteves, Giovanni ^[1];

^[3]; Furman, Marschall ^[1]; Reich, Brian J. ^[1]

North Carolina State Univ., Raleigh, NC (United States)
Virginia Commonwealth Univ., Richmond, VA (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Motivated by the problem of detecting changes in two-dimensional X-ray diffraction data, we propose a Bayesian spatial model for sparse signal detection in image data. Our model places considerable mass near zero and has heavy tails to reflect the prior belief that the image signal is zero for most pixels and large for an important subset. We show that the spatial prior places mass on nearby locations simultaneously being zero, and also allows for nearby locations to simultaneously be large signals. The form of the prior also facilitates efficient computing for large images. We conduct a simulation study to evaluate the properties of the proposed prior and show that it outperforms other spatial models. As a result, we apply our method in the analysis of X-ray diffraction data from a two-dimensional area detector to detect changes in the pattern when the material is exposed to an electric field.

View Accepted Manuscript (DOE)

Cite

Export

Save

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1504020

Journal Information:: Technometrics, Vol. 61, Issue 4; ISSN 0040-1706

Publisher:: Taylor & FrancisCopyright Statement

Country of Publication:: United States

Language:: English

Citation Metrics:

Cited by: 3 works

Citation information provided by
Web of Science

References (55)

Inference with normal-gamma prior distributions in regression problems Griffin, Jim E.; Brown, Philip J. Bayesian Analysis, Vol. 5, Issue 1 https://doi.org/10.1214/10-BA507	journal	March 2010
Interpolation of Spatial Data Stein, Michael L. Springer Series in Statistics https://doi.org/10.1007/978-1-4612-1494-6	book	January 1999
Spatial variable selection methods for investigating acute health effects of fine particulate matter components: Spatial Variable Selection for Effects of PM Components Boehm Vock, Laura F.; Reich, Brian J.; Fuentes, Montserrat Biometrics, Vol. 71, Issue 1 https://doi.org/10.1111/biom.12254	journal	October 2014
The what, how, and why of wavelet shrinkage denoising Taswell, C. Computing in Science & Engineering, Vol. 2, Issue 3 https://doi.org/10.1109/5992.841791	journal	January 2000
Variable Selection via Gibbs Sampling George, Edward I.; McCulloch, Robert E. Journal of the American Statistical Association, Vol. 88, Issue 423 https://doi.org/10.1080/01621459.1993.10476353	journal	September 1993
The horseshoe estimator: Posterior concentration around nearly black vectors van der Pas, S. L.; Kleijn, B. J. K.; van der Vaart, A. W. Electronic Journal of Statistics, Vol. 8, Issue 2 https://doi.org/10.1214/14-EJS962	journal	January 2014
Bayesian Variable Selection in Linear Regression Mitchell, T. J.; Beauchamp, J. J. Journal of the American Statistical Association, Vol. 83, Issue 404 https://doi.org/10.1080/01621459.1988.10478694	journal	December 1988
Anomaly Detection in Images With Smooth Background via Smooth-Sparse Decomposition Yan, Hao; Paynabar, Kamran; Shi, Jianjun Technometrics, Vol. 59, Issue 1 https://doi.org/10.1080/00401706.2015.1102764	journal	January 2017
In situ characterization of polycrystalline ferroelectrics using x-ray and neutron diffraction Esteves, Giovanni; Fancher, Chris M.; Jones, Jacob L. Journal of Materials Research, Vol. 30, Issue 3 https://doi.org/10.1557/jmr.2014.302	journal	November 2014
Ideal spatial adaptation by wavelet shrinkage Donoho, David L.; Johnstone, Iain M. Biometrika, Vol. 81, Issue 3 https://doi.org/10.1093/biomet/81.3.425	journal	September 1994
Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review Rawat, Waseem; Wang, Zenghui Neural Computation, Vol. 29, Issue 9 https://doi.org/10.1162/neco_a_00990	journal	September 2017
The Estimation of Prediction Error: Covariance Penalties and Cross-Validation Efron, Bradley Journal of the American Statistical Association, Vol. 99, Issue 467 https://doi.org/10.1198/016214504000000692	journal	September 2004
Efficient Empirical Bayes Variable Selection and Estimation in Linear Models Yuan, Ming; Lin, Yi Journal of the American Statistical Association, Vol. 100, Issue 472 https://doi.org/10.1198/016214505000000367	journal	December 2005
Application of the Radon transform to detect small-targets in sea clutter Carretero-Moya, J.; Gismero-Menoyo, J.; Asensio-López, A. IET Radar, Sonar & Navigation, Vol. 3, Issue 2 https://doi.org/10.1049/iet-rsn:20080123	journal	January 2009
Radon-Fourier Transform for Radar Target Detection, I: Generalized Doppler Filter Bank Xu, Jia; Yu, Ji; Peng, Ying-Ning IEEE Transactions on Aerospace and Electronic Systems, Vol. 47, Issue 2 https://doi.org/10.1109/TAES.2011.5751251	journal	April 2011
Dynamic In Situ X-Ray Diffraction Study of Antiferroelectric–Ferroelectric Phase Transition in Strontium-Modified Lead Zirconate Titanate Ceramics Dutta, I.; Singh, R. N. Integrated Ferroelectrics, Vol. 131, Issue 1 https://doi.org/10.1080/10584587.2011.616441	journal	January 2011
Bayesian Model Selection in High-Dimensional Settings Johnson, Valen E.; Rossell, David Journal of the American Statistical Association, Vol. 107, Issue 498 https://doi.org/10.1080/01621459.2012.682536	journal	June 2012
The horseshoe estimator for sparse signals Carvalho, C. M.; Polson, N. G.; Scott, J. G. Biometrika, Vol. 97, Issue 2 https://doi.org/10.1093/biomet/asq017	journal	April 2010
Asymptotic Properties of Bayes Risk for the Horseshoe Prior Datta, Jyotishka; Ghosh, Jayanta. K. Bayesian Analysis, Vol. 8, Issue 1 https://doi.org/10.1214/13-BA805	journal	March 2013
Convolutional neural networks: an overview and application in radiology Yamashita, Rikiya; Nishio, Mizuho; Do, Richard Kinh Gian Insights into Imaging, Vol. 9, Issue 4 https://doi.org/10.1007/s13244-018-0639-9	journal	June 2018
Default Bayesian analysis with global-local shrinkage priors Bhadra, Anindya; Datta, Jyotishka; Polson, Nicholas G. Biometrika, Vol. 103, Issue 4 https://doi.org/10.1093/biomet/asw041	journal	December 2016
A review of Bayesian variable selection methods: what, how and which O'Hara, R. B.; Sillanpää, M. J. Bayesian Analysis, Vol. 4, Issue 1 https://doi.org/10.1214/09-BA403	journal	March 2009
Smooth Scalar-on-Image Regression via Spatial Bayesian Variable Selection Goldsmith, Jeff; Huang, Lei; Crainiceanu, Ciprian M. Journal of Computational and Graphical Statistics, Vol. 23, Issue 1 https://doi.org/10.1080/10618600.2012.743437	journal	January 2014
False discovery control in large-scale spatial multiple testing Sun, Wenguang; Reich, Brian J.; Tony Cai, T. Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 77, Issue 1 https://doi.org/10.1111/rssb.12064	journal	April 2014
Sparse inverse covariance estimation with the graphical lasso Friedman, J.; Hastie, T.; Tibshirani, R. Biostatistics, Vol. 9, Issue 3 https://doi.org/10.1093/biostatistics/kxm045	journal	December 2007
The Spike-and-Slab LASSO Ročková, Veronika; George, Edward I. Journal of the American Statistical Association, Vol. 113, Issue 521 https://doi.org/10.1080/01621459.2016.1260469	journal	September 2017
The birth of X-ray crystallography Thomas, John Meurig Nature, Vol. 491, Issue 7423 https://doi.org/10.1038/491186a	journal	November 2012
A spatial scan statistic Kulldorff, Martin Communications in Statistics - Theory and Methods, Vol. 26, Issue 6 https://doi.org/10.1080/03610929708831995	journal	January 1997
Real-Time Monitoring of High-Dimensional Functional Data Streams via Spatio-Temporal Smooth Sparse Decomposition Yan, Hao; Paynabar, Kamran; Shi, Jianjun Technometrics, Vol. 60, Issue 2 https://doi.org/10.1080/00401706.2017.1346522	journal	June 2017
An Improved Acceptance Procedure for the Hybrid Monte Carlo Algorithm Neal, Radford M. Journal of Computational Physics, Vol. 111, Issue 1 https://doi.org/10.1006/jcph.1994.1054	journal	March 1994
On the determination of functions from their integral values along certain manifolds Radon, Johann IEEE Transactions on Medical Imaging, Vol. 5, Issue 4 https://doi.org/10.1109/TMI.1986.4307775	journal	December 1986
Pathwise coordinate optimization Friedman, Jerome; Hastie, Trevor; Höfling, Holger The Annals of Applied Statistics, Vol. 1, Issue 2 https://doi.org/10.1214/07-AOAS131	journal	December 2007
High-resolution x-ray diffraction study of single crystals of lead zirconate titanate Gorfman, S.; Keeble, D. S.; Glazer, A. M. Physical Review B, Vol. 84, Issue 2 https://doi.org/10.1103/PhysRevB.84.020102	journal	July 2011
Adaptive Thresholding using the Integral Image Bradley, Derek; Roth, Gerhard Journal of Graphics Tools, Vol. 12, Issue 2 https://doi.org/10.1080/2151237X.2007.10129236	journal	January 2007
Spatial Modeling With Spatially Varying Coefficient Processes Gelfand, Alan E.; Kim, Hyon-Jung; Sirmans, C. F. Journal of the American Statistical Association, Vol. 98, Issue 462 https://doi.org/10.1198/016214503000170	journal	June 2003
Scalar-on-image regression via the soft-thresholded Gaussian process Kang, Jian; Reich, Brian J.; Staicu, Ana-Maria Biometrika, Vol. 105, Issue 1 https://doi.org/10.1093/biomet/asx075	journal	January 2018
The Distribution of the Size of the Maximum Cluster of Points on a Line Naus, Joseph I. Journal of the American Statistical Association, Vol. 60, Issue 310 https://doi.org/10.1080/01621459.1965.10480810	journal	June 1965
Spatial Bayesian variable selection and grouping for high-dimensional scalar-on-image regression Li, Fan; Zhang, Tingting; Wang, Quanli The Annals of Applied Statistics, Vol. 9, Issue 2 https://doi.org/10.1214/15-AOAS818	journal	June 2015
Jump Detection in Regression Surfaces Qiu, Peihua; Yandell, Brian Journal of Computational and Graphical Statistics, Vol. 6, Issue 3 https://doi.org/10.2307/1390737	journal	September 1997
BaySTDetect: detecting unusual temporal patterns in small area data via Bayesian model choice Li, G.; Best, N.; Hansell, A. L. Biostatistics, Vol. 13, Issue 4 https://doi.org/10.1093/biostatistics/kxs005	journal	March 2012
An integrated index for identification of fatty liver disease using radon transform and discrete cosine transform features in ultrasound images Acharya, U. Rajendra; Fujita, Hamido; Sudarshan, Vidya K. Information Fusion, Vol. 31 https://doi.org/10.1016/j.inffus.2015.12.007	journal	September 2016
Radon-Domain Detection of the Nipple and the Pectoral Muscle in Mammograms Kinoshita, S. K.; Azevedo-Marques, P. M.; Pereira, R. R. Journal of Digital Imaging, Vol. 21, Issue 1 https://doi.org/10.1007/s10278-007-9035-6	journal	April 2007
Bayesian Methods for High Dimensional Linear Models Nengjun Yi, Himel Mallick Journal of Biometrics & Biostatistics https://doi.org/10.4172/2155-6180.S1-005	journal	January 2013
Automatic assessment of macular edema from color retinal images Deepak, K. S.; Sivaswamy, J. IEEE Transactions on Medical Imaging, Vol. 31, Issue 3 https://doi.org/10.1109/TMI.2011.2178856	journal	March 2012
Uncertainty Quantification for the Horseshoe (with Discussion) van der Pas, Stéphanie; Szabó, Botond; van der Vaart, Aad Bayesian Analysis, Vol. 12, Issue 4 https://doi.org/10.1214/17-BA1065	journal	December 2017
Blur kernel estimation using the radon transform Cho, Taeg Sang; Paris, Sylvain; Horn, Berthold K. P. 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), CVPR 2011 https://doi.org/10.1109/CVPR.2011.5995479	conference	June 2011
Bayesian Variable Selection in Linear Regression Mitchell, T. J.; Beauchamp, J. J. Journal of the American Statistical Association, Vol. 83, Issue 404 https://doi.org/10.2307/2290129	journal	December 1988
Jump Detection in Regression Surfaces Qiu, Peihua; Yandell, Brian Journal of Computational and Graphical Statistics, Vol. 6, Issue 3 https://doi.org/10.1080/10618600.1997.10474746	journal	September 1997
Interpolation of Spatial Data Aliyev, Rae Zh Biomedical Journal of Scientific & Technical Research, Vol. 9, Issue 1 https://doi.org/10.26717/bjstr.2018.09.001746	journal	September 2018
The Spike-and-Slab LASSO Ročková, Veronika; George, Edward I. Taylor & Francis https://doi.org/10.6084/m9.figshare.4478396.v4	text	January 2019
The Spike-and-Slab LASSO Ročková, Veronika; George, Edward I. Taylor & Francis https://doi.org/10.6084/m9.figshare.4478396	text	January 2019
The Spike-and-Slab LASSO Ročková, Veronika; George, Edward I. Taylor & Francis https://doi.org/10.6084/m9.figshare.4478396.v2	text	January 2018
The Horseshoe Estimator: Posterior Concentration around Nearly Black Vectors van der Pas, S. L.; Kleijn, B. J. K.; van der Vaart, A. W. arXiv https://doi.org/10.48550/arxiv.1404.0202	text	January 2014
Spatial Bayesian variable selection and grouping for high-dimensional scalar-on-image regression Li, Fan; Zhang, Tingting; Wang, Quanli arXiv https://doi.org/10.48550/arxiv.1509.04069	text	January 2015
Default Bayesian analysis with global-local shrinkage priors Bhadra, Anindya; Datta, Jyotishka; Polson, Nicholas G. arXiv https://doi.org/10.48550/arxiv.1510.03516	preprint	January 2015

Similar Records

Experimental demonstration of direct L-shell x-ray fluorescence imaging of gold nanoparticles using a benchtop x-ray source

Journal Article · Thu Aug 15 00:00:00 EDT 2013 · Medical Physics · OSTI ID:1504020

Manohar, Nivedh; Reynoso, Francisco J.; Cho, Sang Hyun

Bayesian Approach to Estimation of Water Table Elevations Using Historical Rasters as Prior Information 2019 - 20430

Conference · Wed Jul 01 00:00:00 EDT 2020 · OSTI ID:1504020

Carson, John; Jordan, Amy; Rice, Amy; +4 more

The missing GeV γ-ray binary: Searching for HESS J0632+057 with Fermi-LAT

Journal Article · Wed Sep 25 00:00:00 EDT 2013 · Monthly Notices of the Royal Astronomical Society · OSTI ID:1504020

Caliandro, G. A.; Hill, A. B.; Torres, D. F.; +13 more

Related Subjects

97 MATHEMATICS AND COMPUTING
Bayesian variable selection
High-dimensional data
Image analysis
X-ray diffraction

Spatial Signal Detection Using Continuous Shrinkage Priors Jhuang, An-Ting; Fuentes, Montserrat; Jones, Jacob L. https://doi.org/10.6084/m9.figshare.7491635 The current record is supplemented by this dataset	dataset	January 2018
Spatial Signal Detection Using Continuous Shrinkage Priors Jhuang, An-Ting; Fuentes, Montserrat; Jones, Jacob L. https://doi.org/10.6084/m9.figshare.7491635.v1 The current record is supplemented by this dataset	dataset	January 2018

Title: Spatial Signal Detection Using Continuous Shrinkage Priors

Citation Formats

References (55)

Linked Research (2)

Similar Records

Related Subjects