@article{li2020an,
  title = {Anisotropy of {{Magnetic Susceptibility}} ({{AMS}}) {{Analysis}} of the {{Gonjo Basin}} as an {{Independent Constraint}} to {{Date Tibetan Shortening Pulses}}},
  author = {Li, Shihu and {van Hinsbergen}, Douwe J. J. and Shen, Zhongshan and Najman, Yani and Deng, Chenglong and Zhu, Rixiang},
  year = 2020,
  journal = {Geophysical Research Letters},
  volume = {47},
  number = {8},
  pages = {e2020GL087531},
  doi = {10.1029/2020GL087531},
  abstract = {The Tibetan Plateau accommodated major upper crustal shortening during Indian Plate oceanic and continental lithosphere subduction. Deciphering whether shortening was continuous or episodic, and how it correlates to major geodynamic changes is challenging. Here we apply anisotropy of magnetic susceptibility (AMS), a sensitive synsedimentary strain indicator, to a 3 km thick magnetostratigraphically dated sedimentary section (69--41.5 Ma) in eastern Tibet. AMS shows ``earliest deformation'' fabrics from 69--52 Ma, followed by a sudden change to ``pencil structure'' fabrics with increasing anisotropy degree at 52 Ma, dating a sudden increased synsedimentary shortening strain. This change coincides with enhanced sedimentation rates and synsedimentary vertical-axis rotations of the Gonjo Basin, suggesting a causal link to a marked India-Asia convergence rate deceleration. We show that AMS analysis provides a strong tool to distinguish between climatic and tectonic causes of sedimentological change and is an asset in identifying discrete tectonic pulses in intensely deformed terrane.},
  copyright = {\copyright 2020. American Geophysical Union. All Rights Reserved.}
}


@article{owen:2013,
  title={Self-concordance for empirical likelihood},
  author={Owen, A. B.},
  journal={Canadian Journal of Statistics},
  volume={41},
  number={3},
  pages={387--397},
  year={2013}
}

@article{schwartzman2008in,
  title = {Inference for {{Eigenvalues}} and {{Eigenvectors}} of {{Gaussian Symmetric Matrices}}},
  author = {Schwartzman, Armin and Mascarenhas, Walter F. and Taylor, Jonathan E.},
  year = {2008},
  journal = {The Annals of Statistics},
  volume = {36},
  number = {6},
  pages = {2886--2919},
  publisher = {Institute of Mathematical Statistics},
  url = {https://www.jstor.org/stable/25464736}
}

@article{schwartzman2010gr,
  title = {Group {{Comparison}} of {{Eigenvalues}} and {{Eigenvectors}} of {{Diffusion Tensors}}},
  author = {Schwartzman, Armin and Dougherty, Robert F. and Taylor, Jonathan E.},
  year = {2010},
  month = jun,
  journal = {Journal of the American Statistical Association},
  volume = {105},
  number = {490},
  pages = {588--599},
  publisher = {Taylor \& Francis},
  doi = {10.1198/jasa.2010.ap07291},
  url = {https://doi.org/10.1198/jasa.2010.ap07291}
}

@article{lin1972ch,
  title = {Some characterizations of the multivariate t distribution},
  author = {Lin, Pi-Erh},
  year = {1972},
  journal = {Journal of Multivariate Analysis},
  volume = {2},
  number = {3},
  pages = {339--344},
  doi = {10.1016/0047-259X(72)90021-8}
}

@book{magnus2019ma,
  title = {Matrix {{Differential Calculus}} with {{Applications}} in {{Statistics}} and {{Econometrics}}, 3rd {{Edition}}},
  author = {Magnus, Jan R. and Neudecker, Heinz},
  year = {2019},
  edition = {3},
  publisher = {John Wiley and Sons Ltd},
  url = {https://learning.oreilly.com/library/view/matrix-differential-calculus/9781119541202/},
  urldate = {2023-02-15},
  abstract = {A brand new, fully updated edition of a popular classic on matrix differential calculus with applications in statistics and econometrics This exhaustive, self-contained book on matrix theory and...},
  isbn = {978-1-119-54120-2}
}

@article{hall1999in,
  title = {Intentionally {{Biased Bootstrap Methods}}},
  author = {Hall, Peter and Presnell, Brett},
  year = {1999},
  journal = {Journal of the Royal Statistical Society. Series B (Statistical Methodology)},
  volume = {61},
  number = {1},
  eprint = {2680742},
  eprinttype = {jstor},
  pages = {143--158},
  publisher = {[Royal Statistical Society, Oxford University Press]},
  issn = {1369-7412},
  url = {https://www.jstor.org/stable/2680742},
  urldate = {2025-02-04},
  abstract = {A class of weighted bootstrap techniques, called biased bootstrap or b-bootstrap methods, is introduced. It is motivated by the need to adjust empirical methods, such as the 'uniform' bootstrap, in a surgical way to alter some of their features while leaving others unchanged. Depending on the nature of the adjustment, the b-bootstrap can be used to reduce bias, or to reduce variance or to render some characteristic equal to a predetermined quantity. Examples of the last application include a b-bootstrap approach to hypothesis testing in nonparametric contexts, where the b-bootstrap enables simulation 'under the null hypothesis', even when the hypothesis is false, and a b-bootstrap competitor to Tibshirani's variance stabilization method. An example of the bias reduction application is adjustment of Nadaraya-Watson kernel estimators to make them competitive with local linear smoothing. Other applications include density estimation under constraints, outlier trimming, sensitivity analysis, skewness or kurtosis reduction and shrinkage.}
}

@article{hingee2026no,
  title = {Nonparametric bootstrap inference for the eigenvalues of geophysical tensors},
  author = {Kassel L. Hingee and Janice L. Scealy and Andrew T.A. Wood},
  year = {2026},
  journal = {Journal of American Statistical Association},
  doi = {10.1080/01621459.2025.2606381},
  pages = {1-13}
}

