Matches in SemOpenAlex for { <https://semopenalex.org/work/W2309591796> ?p ?o ?g. }
Showing items 1 to 69 of
69
with 100 items per page.
- W2309591796 abstract "Precision matrices play important roles in many statistical applications. We consider the statistical inference for precision matrices with ultra high-dimensional time dependent observations. More specifically, let $boldsymbol{Omega}$ be the precision matrix and $mathcal{S}$ be a given index set of interest. We propose a data-driven procedure to construct a class of confidence regions $mathcal{C}_{mathcal{S},alpha}$ for $boldsymbol{Omega}_{mathcal{S}}$ such that $sup_{0<alpha<1} |mathbb{P}(boldsymbol{Omega}_{mathcal{S}}inmathcal{C}_{mathcal{S},alpha})-alpha|rightarrow0$ as $nrightarrowinfty$, where $boldsymbol{Omega}_{mathcal{S}}$ is a vector whose components are the elements of $boldsymbol{Omega}$ indexed by $mathcal{S}$. The proposed procedure includes two steps. We first derive an estimator $widehat{boldsymbol{Omega}}_{mathcal{S}}$ for $boldsymbol{Omega}_{mathcal{S}}$ via penalized node-wise regressions, and then approximate the distribution of $n^{1/2}|widehat{boldsymbol{Omega}}_{mathcal{S}}-boldsymbol{Omega}_{mathcal{S}}|_infty$ by that of the $l_infty$-norm of an ultra high-dimensional Gaussian random vector with mean zero and covariance formulated as an estimate for the long-run covariance of an unobservable process. Our analysis shows that the kernel-type estimator initially suggested by Andrews (1991) for the fixed dimensional long-run covariance can be also employed in the proposed procedure for the ultra high-dimensional scenario without imposing any additional stringent structural assumptions on the long-run covariance. Owing to the form of the kernel-type estimator, we develop a computationally feasible algorithm to implement the proposed procedure. Theoretical analysis shows the proposed procedure works well even without imposing the stationary assumption on the data." @default.
- W2309591796 created "2016-06-24" @default.
- W2309591796 creator A5012472156 @default.
- W2309591796 creator A5021528183 @default.
- W2309591796 creator A5057369634 @default.
- W2309591796 date "2016-03-22" @default.
- W2309591796 modified "2023-09-27" @default.
- W2309591796 title "On the statistical inference for large precision matrices with dependent data" @default.
- W2309591796 cites W2096526352 @default.
- W2309591796 cites W2108446661 @default.
- W2309591796 hasPublicationYear "2016" @default.
- W2309591796 type Work @default.
- W2309591796 sameAs 2309591796 @default.
- W2309591796 citedByCount "2" @default.
- W2309591796 countsByYear W23095917962017 @default.
- W2309591796 countsByYear W23095917962019 @default.
- W2309591796 crossrefType "posted-content" @default.
- W2309591796 hasAuthorship W2309591796A5012472156 @default.
- W2309591796 hasAuthorship W2309591796A5021528183 @default.
- W2309591796 hasAuthorship W2309591796A5057369634 @default.
- W2309591796 hasConcept C105795698 @default.
- W2309591796 hasConcept C114614502 @default.
- W2309591796 hasConcept C121332964 @default.
- W2309591796 hasConcept C178650346 @default.
- W2309591796 hasConcept C185429906 @default.
- W2309591796 hasConcept C18903297 @default.
- W2309591796 hasConcept C2777299769 @default.
- W2309591796 hasConcept C2779557605 @default.
- W2309591796 hasConcept C33923547 @default.
- W2309591796 hasConcept C62520636 @default.
- W2309591796 hasConcept C86803240 @default.
- W2309591796 hasConceptScore W2309591796C105795698 @default.
- W2309591796 hasConceptScore W2309591796C114614502 @default.
- W2309591796 hasConceptScore W2309591796C121332964 @default.
- W2309591796 hasConceptScore W2309591796C178650346 @default.
- W2309591796 hasConceptScore W2309591796C185429906 @default.
- W2309591796 hasConceptScore W2309591796C18903297 @default.
- W2309591796 hasConceptScore W2309591796C2777299769 @default.
- W2309591796 hasConceptScore W2309591796C2779557605 @default.
- W2309591796 hasConceptScore W2309591796C33923547 @default.
- W2309591796 hasConceptScore W2309591796C62520636 @default.
- W2309591796 hasConceptScore W2309591796C86803240 @default.
- W2309591796 hasLocation W23095917961 @default.
- W2309591796 hasOpenAccess W2309591796 @default.
- W2309591796 hasPrimaryLocation W23095917961 @default.
- W2309591796 hasRelatedWork W1518923106 @default.
- W2309591796 hasRelatedWork W1935999090 @default.
- W2309591796 hasRelatedWork W2040482074 @default.
- W2309591796 hasRelatedWork W2098916533 @default.
- W2309591796 hasRelatedWork W2159416808 @default.
- W2309591796 hasRelatedWork W2248523368 @default.
- W2309591796 hasRelatedWork W2258740267 @default.
- W2309591796 hasRelatedWork W2512248760 @default.
- W2309591796 hasRelatedWork W2545080023 @default.
- W2309591796 hasRelatedWork W2589999127 @default.
- W2309591796 hasRelatedWork W2801027322 @default.
- W2309591796 hasRelatedWork W2888153825 @default.
- W2309591796 hasRelatedWork W2913392575 @default.
- W2309591796 hasRelatedWork W2913473024 @default.
- W2309591796 hasRelatedWork W2950757834 @default.
- W2309591796 hasRelatedWork W3014457793 @default.
- W2309591796 hasRelatedWork W3049025113 @default.
- W2309591796 hasRelatedWork W3093110333 @default.
- W2309591796 hasRelatedWork W3110221193 @default.
- W2309591796 hasRelatedWork W59808842 @default.
- W2309591796 isParatext "false" @default.
- W2309591796 isRetracted "false" @default.
- W2309591796 magId "2309591796" @default.
- W2309591796 workType "article" @default.