Zhou Lan

Works (3)

Updated: August 28th, 2023 21:16

2021 article

A spatial Bayesian semiparametric mixture model for positive definite matrices with applications in diffusion tensor imaging

Lan, Z., Reich, B. J., & Bandyopadhyay, D. (2021, January 25). Canadian Journal of Statistics.

By: Z. Lan n, B. Reich n  & D. Bandyopadhyay

Contributors: Z. Lan n, B. Reich n  & D. Bandyopadhyay

author keywords: Diffusion tensor imaging; inverse Wishart distribution; matrix variate; positive definite matrix; spatial statistics
topics (OpenAlex): Advanced Neuroimaging Techniques and Applications; Bayesian Methods and Mixture Models; Tensor decomposition and applications; Point processes and geometric inequalities
TL;DR: A matrix‐variate Bayesian semiparametric mixture model is proposed, where the p.d. matrices are distributed as a mixture of inverse Wishart distributions, with the spatial dependence captured by a Markov model for the mixture component labels. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries, ORCID
Added: February 15, 2021

2021 article

Geostatistical modeling of positive‐definite matrices: An application to diffusion tensor imaging

Lan, Z., Reich, B. J., Guinness, J., Bandyopadhyay, D., Ma, L., & Moeller, F. G. (2021, February 11). Biometrics.

By: Z. Lan*, B. Reich n , J. Guinness*, D. Bandyopadhyay *, L. Ma * & F. Moeller *

Contributors: Z. Lan*, B. Reich n , J. Guinness*, D. Bandyopadhyay *, L. Ma * & F. Moeller *

author keywords: Cholesky decomposition; diffusion tensor imaging; geostatistical modeling; positive‐ definite matrix; spatial random fields; spatial Wishart process
MeSH headings : Computer Simulation; Diffusion Tensor Imaging; Normal Distribution; Stochastic Processes
topics (OpenAlex): Advanced Neuroimaging Techniques and Applications; Point processes and geometric inequalities; Spatial and Panel Data Analysis
TL;DR: An approximation method is proposed to obtain a feasible Cholesky decomposition model, which is shown to be asymptotically equivalent to the spatial Wishart process model and to produce reliable inference and improved performance, compared to other methods. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries, ORCID
Added: March 8, 2021

2016 journal article

Bayesian network feature finder (BANFF): an r package for gene network feature selection

Bioinformatics, 32(23), 3685–3687.

By: Z. Lan, Y. Zhao, J. Kang & T. Yu

Source: NC State University Libraries
Added: August 6, 2018

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