How To Install "r-cran-rms" Package on Ubuntu
Quick Install Instructions of r-cran-rms 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-rms
Step 3
Check the system logs to confirm that there are no related errors.
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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 regression modeling strategies by Frank Harrell
Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. rms is a collection of 229 functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. rms works with almost any regression model, but it was especially written to work with binary or ordinal logistic regression, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression. GNU R regression modeling strategies by Frank Harrell
Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. rms is a collection of 229 functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. rms works with almost any regression model, but it was especially written to work with binary or ordinal logistic regression, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression.
Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. rms is a collection of 229 functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. rms works with almost any regression model, but it was especially written to work with binary or ordinal logistic regression, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression. GNU R regression modeling strategies by Frank Harrell
Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. rms is a collection of 229 functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. rms works with almost any regression model, but it was especially written to work with binary or ordinal logistic regression, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression.
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-rms
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.