Cargando…
De-Biased Graphical Lasso for High-Frequency Data
This paper develops a new statistical inference theory for the precision matrix of high-frequency data in a high-dimensional setting. The focus is not only on point estimation but also on interval estimation and hypothesis testing for entries of the precision matrix. To accomplish this purpose, we e...
Autor principal: | Koike, Yuta |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516938/ https://www.ncbi.nlm.nih.gov/pubmed/33286230 http://dx.doi.org/10.3390/e22040456 |
Ejemplares similares
-
Analysis of Twitter data with the Bayesian fused graphical lasso
por: Aflakparast, Mehran, et al.
Publicado: (2020) -
Extended graphical lasso for multiple interaction networks for high dimensional omics data
por: Xu, Yang, et al.
Publicado: (2021) -
Tailored graphical lasso for data integration in gene network reconstruction
por: Lingjærde, Camilla, et al.
Publicado: (2021) -
Graphical modeling of binary data using the LASSO: a simulation study
por: Strobl, Ralf, et al.
Publicado: (2012) -
Efficient Proximal Gradient Algorithms for Joint Graphical Lasso
por: Chen, Jie, et al.
Publicado: (2021)