Journal article
Australian \& New Zealand Journal of Statistics, vol. 64, 2022, pp. 313-337
APA
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Zhang, H., Swallow, B., & Gupta, M. (2022). Bayesian hierarchical mixture models for detecting non-normal clusters applied to noisy genomic and environmental datasets. Australian \&Amp; New Zealand Journal of Statistics, 64, 313–337. https://doi.org/10.1111/anzs.12370
Chicago/Turabian
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Zhang, Huizi, Ben Swallow, and Mayetri Gupta. “Bayesian Hierarchical Mixture Models for Detecting Non-Normal Clusters Applied to Noisy Genomic and Environmental Datasets.” Australian \& New Zealand Journal of Statistics 64 (2022): 313–337.
MLA
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Zhang, Huizi, et al. “Bayesian Hierarchical Mixture Models for Detecting Non-Normal Clusters Applied to Noisy Genomic and Environmental Datasets.” Australian \&Amp; New Zealand Journal of Statistics, vol. 64, 2022, pp. 313–37, doi:10.1111/anzs.12370.
BibTeX Click to copy
@article{zhang2022a,
title = {Bayesian hierarchical mixture models for detecting non-normal clusters applied to noisy genomic and environmental datasets},
year = {2022},
journal = {Australian \& New Zealand Journal of Statistics},
pages = {313-337},
volume = {64},
doi = {10.1111/anzs.12370},
author = {Zhang, Huizi and Swallow, Ben and Gupta, Mayetri}
}