Large Sample Theory of Intrinsic and Extrinsic Sample Means on Manifolds: II

Autor: Bhattacharya, Rabi, Patrangenaru, Vic

Publikováno v: The Annals of Statistics, 2005 Jun 01. 33(3), 1225-1259.

Externí odkaz: https://www.jstor.org/stable/3448687

Manifold valued data analysis of samples of networks, with applications in corpus linguistics

Autor: Katie E. Severn, Ian L. Dryden, Simon P. Preston

Networks arise in many applications, such as in the analysis of text documents, social interactions and brain activity. We develop a general framework for extrinsic statistical analysis of samples of networks, motivated by networks representing text

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::506f9d89515a7683007ea358b8f4be46

Sample Mean Versus Sample Fréchet Mean for Combining Complex Wishart Matrices: A Statistical Study

Autor: L. Zhuang, Andrew T. Walden

Publikováno v: IEEE Transactions on Signal Processing. 65:4551-4561

The space of covariance matrices is a non-Euclidean space. The matrices form a manifold which if equipped with a Riemannian metric becomes a Riemannian manifold, and recently this idea has been used for comparison and clustering of complex valued spe

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9f039d82e8299ebcf83ca0d2b21616b5
https://doi.org/10.1109/tsp.2017.2713763

An order fitting rule for optimal subspace averaging

Autor: Joseph M. Francos, Louis L. Scharf, Chris Peterson, Ignacio Santamaria, Michael Kirby

Publikováno v: IEEE Workshop on Statistical Signal Processing (SSP), Palma de Mallorca, 2016, 675-678
SSP
UCrea Repositorio Abierto de la Universidad de Cantabria
Universidad de Cantabria (UC)

The problem of estimating a low-dimensional subspace from a collection of experimentally measured subspaces arises in many applications of statistical signal processing. In this paper we address this problem, and give a solution for the average subsp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34b1969148e2bc4da7860d243afcd156
http://hdl.handle.net/10902/11090

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