How To Install "r-cran-corpcor" Package on Ubuntu
Quick Install Instructions of r-cran-corpcor on Ubuntu Server. It’s Super Easy! simply click on Copy button to copy the command and paste into your command line terminal using built-in APT package manager.
See below for quick step by step instructions of SSH commands, Copy/Paste to avoid miss-spelling or accidently installing a different package.
See below for quick step by step instructions of SSH commands, Copy/Paste to avoid miss-spelling or accidently installing a different package.
Quick Install Steps:
Step 1
sudo apt-get update -y
Step 2
sudo apt-get install -y r-cran-corpcor
Step 3
Check the system logs to confirm that there are no related errors.
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to check the logs, manager servers, host multiple websites and apps on your servers and more. The apps run in docker containers, to learn more
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see ZoomAdmin Features for list of features and demo videos. And you can start with the Free Plan.
Execute the commands above step by step.
You can simply hit the copy button to copy the command and paste into the command line interface.
Note: -y flag means to assume yes and silently install, without asking you questions in most cases.
Note: -y flag means to assume yes and silently install, without asking you questions in most cases.
GNU R for Estimation of Covariance and Correlation -- corpcor
GNU R package which implements a James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations. The approach is both computationally as well as statistically very efficient, it is applicable to "small n, large p" data, and always returns a positive definite and well-conditioned covariance matrix. In addition to inferring the covariance matrix the package also provides shrinkage estimators for partial correlations and partial variances. The inverse of the covariance and correlation matrix can be efficiently computed, as well as any arbitrary power of the shrinkage correlation matrix. Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse, and for checking the rank and positive definiteness of a matrix. GNU R for Estimation of Covariance and Correlation -- corpcor
GNU R package which implements a James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations. The approach is both computationally as well as statistically very efficient, it is applicable to "small n, large p" data, and always returns a positive definite and well-conditioned covariance matrix. In addition to inferring the covariance matrix the package also provides shrinkage estimators for partial correlations and partial variances. The inverse of the covariance and correlation matrix can be efficiently computed, as well as any arbitrary power of the shrinkage correlation matrix. Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse, and for checking the rank and positive definiteness of a matrix.
GNU R package which implements a James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations. The approach is both computationally as well as statistically very efficient, it is applicable to "small n, large p" data, and always returns a positive definite and well-conditioned covariance matrix. In addition to inferring the covariance matrix the package also provides shrinkage estimators for partial correlations and partial variances. The inverse of the covariance and correlation matrix can be efficiently computed, as well as any arbitrary power of the shrinkage correlation matrix. Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse, and for checking the rank and positive definiteness of a matrix. GNU R for Estimation of Covariance and Correlation -- corpcor
GNU R package which implements a James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations. The approach is both computationally as well as statistically very efficient, it is applicable to "small n, large p" data, and always returns a positive definite and well-conditioned covariance matrix. In addition to inferring the covariance matrix the package also provides shrinkage estimators for partial correlations and partial variances. The inverse of the covariance and correlation matrix can be efficiently computed, as well as any arbitrary power of the shrinkage correlation matrix. Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse, and for checking the rank and positive definiteness of a matrix.
Detailed Instructions:
Step 1
Run update command to update package repositories and get latest package information.
sudo apt-get update -y
Step 2
Run the install command with -y flag to quickly install the packages and dependencies.
sudo apt-get install -y r-cran-corpcor
Step 3
Check the system logs to confirm that there are no related errors.
You can use
ZoomAdmin
to check the logs, manager servers, host multiple websites and apps on your servers and more. The apps run in docker containers, to learn more
see ZoomAdmin Features for list of features and demo videos. And you can start with the Free Plan.
see ZoomAdmin Features for list of features and demo videos. And you can start with the Free Plan.