您可以简单地使用setdiff函数获取未安装的包，然后安装它们。在下面的示例中，我们在安装ggplot2和Rcpp包之前检查它们是否已经安装。

unavailable <- setdiff(c("ggplot2", "Rcpp"), rownames(installed.packages()))
install.packages(unavailable)

在一行中，上面的内容可以写成:

install.packages(setdiff(c("ggplot2", "Rcpp"), rownames(installed.packages())))

虽然Shane的回答很好，但对于我的一个项目，我需要自动删除输出消息、警告和安装包。我终于设法得到这个脚本:

InstalledPackage <- function(package) 
{
    available <- suppressMessages(suppressWarnings(sapply(package, require, quietly = TRUE, character.only = TRUE, warn.conflicts = FALSE)))
    missing <- package[!available]
    if (length(missing) > 0) return(FALSE)
    return(TRUE)
}

CRANChoosen <- function()
{
    return(getOption("repos")["CRAN"] != "@CRAN@")
}

UsePackage <- function(package, defaultCRANmirror = "http://cran.at.r-project.org") 
{
    if(!InstalledPackage(package))
    {
        if(!CRANChoosen())
        {       
            chooseCRANmirror()
            if(!CRANChoosen())
            {
                options(repos = c(CRAN = defaultCRANmirror))
            }
        }

        suppressMessages(suppressWarnings(install.packages(package)))
        if(!InstalledPackage(package)) return(FALSE)
    }
    return(TRUE)
}

Use:

libraries <- c("ReadImages", "ggplot2")
for(library in libraries) 
{ 
    if(!UsePackage(library))
    {
        stop("Error!", library)
    }
}

我使用以下函数安装包，如果require("<包>")退出包未发现错误。它将查询- CRAN和Bioconductor存储库，以查找丢失的包。

改编自约书亚·威利的原著， http://r.789695.n4.nabble.com/Install-package-automatically-if-not-there-td2267532.html

install.packages.auto <- function(x) { 
  x <- as.character(substitute(x)) 
  if(isTRUE(x %in% .packages(all.available=TRUE))) { 
    eval(parse(text = sprintf("require(\"%s\")", x)))
  } else { 
    #update.packages(ask= FALSE) #update installed packages.
    eval(parse(text = sprintf("install.packages(\"%s\", dependencies = TRUE)", x)))
  }
  if(isTRUE(x %in% .packages(all.available=TRUE))) { 
    eval(parse(text = sprintf("require(\"%s\")", x)))
  } else {
    source("http://bioconductor.org/biocLite.R")
    #biocLite(character(), ask=FALSE) #update installed packages.
    eval(parse(text = sprintf("biocLite(\"%s\")", x)))
    eval(parse(text = sprintf("require(\"%s\")", x)))
  }
}

例子:

install.packages.auto(qvalue) # from bioconductor
install.packages.auto(rNMF) # from CRAN

注:更新。packages(ask =FALSE) & biocLite(character()， ask=FALSE)将更新系统上所有已安装的软件包。这可能需要很长时间，并将其视为一个完整的R升级，这可能并不总是有保障的!

今天，我偶然发现了rlang包提供的两个方便函数，即is_installed()和check_installed()。

从帮助页面(强调添加):

These functions check that packages are installed with minimal side effects. If installed, the packages will be loaded but not attached. is_installed() doesn't interact with the user. It simply returns TRUE or FALSE depending on whether the packages are installed. In interactive sessions, check_installed() asks the user whether to install missing packages. If the user accepts, the packages are installed [...]. If the session is non interactive or if the user chooses not to install the packages, the current evaluation is aborted.

interactive()
#> [1] FALSE
rlang::is_installed(c("dplyr"))
#> [1] TRUE
rlang::is_installed(c("foobarbaz"))
#> [1] FALSE
rlang::check_installed(c("dplyr"))
rlang::check_installed(c("foobarbaz"))
#> Error:
#> ! The package `foobarbaz` is required.

由reprex包在2022-03-25创建(v2.0.1)

source("https://bioconductor.org/biocLite.R")
if (!require("ggsci")) biocLite("ggsci")

我使用以下将检查包是否安装和依赖项是否更新，然后加载包。

p<-c('ggplot2','Rcpp')
install_package<-function(pack)
{if(!(pack %in% row.names(installed.packages())))
{
  update.packages(ask=F)
  install.packages(pack,dependencies=T)
}
 require(pack,character.only=TRUE)
}
for(pack in p) {install_package(pack)}

completeFun <- function(data, desiredCols) {
  completeVec <- complete.cases(data[, desiredCols])
  return(data[completeVec, ])
}