A horseshoe mixture model for Bayesian screening with an application to light sheet fluorescence microscopy in brain imaging-Reference-Cited by-同舟云学术

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A horseshoe mixture model for Bayesian screening with an application to light sheet fluorescence microscopy in brain imaging

Published:2023-09-01 Issue:3 Volume:17 Page:
ISSN:1932-6157
Container-title:The Annals of Applied Statistics
language:
Short-container-title:Ann. Appl. Stat.

Author:

Denti Francesco¹,Azevedo Ricardo²,Lo Chelsie²,Wheeler Damian G.³,Gandhi Sunil P.²,Guindani Michele⁴,Shahbaba Babak⁵

Affiliation:

1. Department of Statistics, Università Cattolica del Sacro Cuore

2. Department of Neurobiology and Behavior, University of California, Irvine

3. Translucence Biosystems, Inc

4. Department of Biostatistcs, University of California, Los Angeles

5. Department of Statistics, University of California, Irvine

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Reference47 articles.

1. Hahn, P. R. and Carvalho, C. M. (2015). Decoupling shrinkage and selection in Bayesian linear models: A posterior summary perspective. J. Amer. Statist. Assoc. 110 435–448.

2. Rousseau, J. and Mengersen, K. (2011). Asymptotic behaviour of the posterior distribution in overfitted mixture models. J. R. Stat. Soc. Ser. B. Stat. Methodol. 73 689–710.

3. MALSINER-WALLI, G., FRÜHWIRTH-SCHNATTER, S. and GRÜN, B. (2016). Model-based clustering based on sparse finite Gaussian mixtures. Stat. Comput. 26 303–324.

4. ANDERMANN, M. L., KERLIN, A. M., ROUMIS, D. K., GLICKFELD, L. L. and REID, R. C. (2011). Functional specialization of mouse higher visual cortical areas. Neuron 72 1025–1039.

5. BHADRA, A., DATTA, J., POLSON, N. G. and WILLARD, B. (2019). Lasso meets horseshoe: A survey. Statist. Sci. 34 405–427.

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