WebBasic Usage. The spack command has many subcommands. You’ll only need a small subset of them for typical usage. Note that Spack colorizes output. less -R should be used with Spack to maintain this colorization. E.g.: $ spack find less -R. It is recommended that the following be put in your .bashrc file: WebFeb 4, 2024 · lsmod Command. lsmod is a simple utility that does not accept any options or arguments. What the command does is that it reads /proc/modules and display the file contents in a nicely formatted list. Run lsmod at the command line to find out what kernel modules are currently loaded: lsmod. The command outputs information for each loaded …
How to check which packages are loaded in R?
WebTo see which version is installed of all loaded packages, just use the above command to subset installed.packages (). installed.packages () [ (.packages ()),3] By changing the … WebDetails. installed.packages scans the ‘ DESCRIPTION ’ files of each package found along lib.loc and returns a matrix of package names, library paths and version numbers.. The information found is cached (by library) for the R session and specified fields argument, and updated only if the top-level library directory has been altered, for example by installing or … incarcare orange online
R: Find Installed Packages - ETH Z
WebThere are several related functions available, which give more information of your installed packages. Two helpful functions are packageDate () and packageDescription (). The packageDate command returns the date of a package. Let’s do this for dplyr: packageDate ("dplyr") # Get date of dplyr # "2024-07-04". With the packageDescription ... WebA summary of the most important commands with minimal examples. See the relevant part of the guide for better examples. For all of these commands ... knowing what to ask for help about is the hardest problem. See the R-reference card by Tom Short for a much more complete list. Input and display #read files with labels in first row ... WebOct 28, 2024 · Logistic regression is a method we can use to fit a regression model when the response variable is binary.. Logistic regression uses a method known as maximum likelihood estimation to find an equation of the following form:. log[p(X) / (1-p(X))] = β 0 + β 1 X 1 + β 2 X 2 + … + β p X p. where: X j: The j th predictor variable; β j: The coefficient … in charge or on charge