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BlockCov  

Estimation of Large Block Covariance Matrices
View on CRAN: Click here


Download and install BlockCov package within the R console
Install from CRAN:
install.packages("BlockCov")

Install from Github:
library("remotes")
install_github("cran/BlockCov")

Install by package version:
library("remotes")
install_version("BlockCov", "0.1.1")



Attach the package and use:
library("BlockCov")
Maintained by
Marie Perrot-Dockès
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-07-01
Latest Update: 2019-04-13
Description:
Computation of large covariance matrices having a block structure up to a permutation of their columns and rows from a small number of samples with respect to the dimension of the matrix. The method is described in the paper Perrot-Dock
How to cite:
Marie Perrot-Dockès (2018). BlockCov: Estimation of Large Block Covariance Matrices. R package version 0.1.1, https://cran.r-project.org/web/packages/BlockCov. Accessed 03 Dec. 2024.
Previous versions and publish date:
0.1.0 (2018-07-01 15:40)
Other packages that cited BlockCov R package
View BlockCov citation profile
Other R packages that BlockCov depends, imports, suggests or enhances
Complete documentation for BlockCov
Functions, R codes and Examples using the BlockCov R package
Some associated functions: BlockCov . PA . Sigma_estimation . Simu_Sigma . cv_bl . est_up . pipe . slope_change . 
Some associated R codes: BlockCov.R . Sigma_estimation.R . Simu_Sigma.R . cv_pa.R . pipe_operator.R . slope_change.R .  Full BlockCov package functions and examples
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