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pro vyhledávání: '"Nurzhan Nurushev"'
Autor:
Eduard Belitser, Nurzhan Nurushev
Publikováno v:
Belitser, E & Nurushev, N 2020, ' Needles and straw in a haystack : Robust confidence for possibly sparse sequences ', Bernoulli, vol. 26, no. 1, pp. 191-225 . https://doi.org/10.3150/19-BEJ1122
Bernoulli 26, no. 1 (2020), 191-225
Bernoulli, 26(1), 191-225. International Statistical Institute
Bernoulli 26, no. 1 (2020), 191-225
Bernoulli, 26(1), 191-225. International Statistical Institute
In the general signal$+$noise (allowing non-normal, non-independent observations) model, we construct an empirical Bayes posterior which we then use for uncertainty quantification for the unknown, possibly sparse, signal. We introduce a novel excessi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98417539c3b40a0bb589c348819f5c60
https://doi.org/10.3150/19-bej1122
https://doi.org/10.3150/19-bej1122
Autor:
Eduard Belitser, Nurzhan Nurushev
Publikováno v:
Bayesian Statistics in Action, 194, 51-66
Springer Proceedings in Mathematics & Statistics ISBN: 9783319540832
Belitser, E N & Nurushev, N 2017, Local posterior concentration rate for multilevel sparse sequences . in Bayesian Statistics in Action . vol. 194, Springer Proceedings in Mathematics & Statistics, Springer, pp. 51-66 . https://doi.org/10.1007/978-3-319-54084-9_6
Springer Proceedings in Mathematics & Statistics ISBN: 9783319540832
Belitser, E N & Nurushev, N 2017, Local posterior concentration rate for multilevel sparse sequences . in Bayesian Statistics in Action . vol. 194, Springer Proceedings in Mathematics & Statistics, Springer, pp. 51-66 . https://doi.org/10.1007/978-3-319-54084-9_6
We consider empirical Bayesian inference in the many normal meansmodel in the situation when the high-dimensional mean vector is multilevel sparse, that is,most of the entries of the parameter vector are some fixed values. For instance, the tradition
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc0ee0109c2a0f816bd024fd731d2631
https://doi.org/10.1007/978-3-319-54084-9_6
https://doi.org/10.1007/978-3-319-54084-9_6
