Question

当我加载我创建的包时，我收到以下警告：

＆＃34;以下对象被掩盖在'package：utils'中：combn＆＃34;

即使我在＆＃34; R＆＃34;的.R文件中的函数定义中使用了combinat :: combn。 R工作目录中的文件夹。

有没有办法摆脱＆＃34; ...对象被屏蔽......＆＃34;警告？（我根本不想掩盖梳理;请参阅Gregor的帖子。）

我添加了＆＃34; combinat ::＆＃34;在我的包中的函数定义中使用前缀，无论我想使用combinat的组合，以便不得到上述警告（将combinat :: combn与utils :: combn混合）。

gctemplate 是包causfinder的一个函数（我删除了＃34; combinat ::＆＃34;对于那些想要掌握这个功能的人;当我抽取＆＃34; combinat：：＆＃34;前缀无论我在函数gctemplate中看到combn，我仍然收到上述警告）：

#' gctemplate
#'
#' Granger causality template for a given system in the desired pattern.
#'
#' Assume a system in which its Granger causality relations among its variables will be searched is given. For the variables of this system (with nvars variables), some varibles may cause (causers, like independents) some others (those that are caused by causers, like dependents) conditional on some others in the system. The function gctemplate has three arguements to list all the possible causation pattern in which Granger causality will be searched. As is known, dependent and independent variables are not specified in the beginning of a Granger analysis, the analysis reveals them.
#'
#' @param nvars integer. The number of all the variables in a given system.
#' @param ncausers integer. The selected number of causer (independent-like) variables
#' @param ndependents integer. The selected number of variables that are caused by the causers, number of dependent-like variables
#' @return granger causality template
#' @author Erdogan Cevher erdogancevher@@gmail.com
#' @seealso \code{\link{conditionalGb}}
#' @examples
#' ## List all G-causalities in a VAR system of 5 variables that will be searched in the pattern of 1 
#' ## causer (like-independent) variable and 2 like-dependents conditional on 5-(1+2)=2 of the remaining 
#' ## variable(s) in the system. Varibles are assigned to numbers 1 to nvars. 
#' ## "1 2 5 3 4" in the rsulting line of gctemplate is to indicate the 
#' ## (conditonal, partial, etc.) G-causality from variable 1 to varibles 2 and 5 
#' ## conditonal on variables 3 and 4.
#' # gctemplate(5,1,2)
#' ## The number of all G-causalities to be searched in the above pattern.
#' #dim(gctemplate(5,1,2))[[1]]
#' @importFrom combinat combn
#' @export
gctemplate <- function(nvars, ncausers, ndependents){  
independents <- combn(nvars, ncausers)  
patinajnumber <-  dim(combn(nvars - ncausers, ndependents))[[2]]  
independentspatinajednumber <- dim(combn(nvars, ncausers))[[2]]*patinajnumber   
dependents <- matrix(, nrow = dim(combn(nvars, ncausers))[[2]]*patinajnumber, ncol = ndependents)  
for (i in as.integer(1:dim(combn(nvars, ncausers))[[2]])){     
dependents[(patinajnumber*(i-1)+1):(patinajnumber*i),] <- t(combn(setdiff(seq(1:nvars), independents[,i]), ndependents))  
}  
independentspatinajed <- matrix(, nrow = dim(combn(nvars, ncausers))[[2]]*patinajnumber, ncol = ncausers)  
for (i in as.integer(1:dim(combn(nvars, ncausers))[[2]])){     
for (j in as.integer(1:patinajnumber)){     
independentspatinajed[(i-1)*patinajnumber+j,] <- independents[,i]    
}}  
independentsdependents <- cbind(independentspatinajed, dependents)  
others <- matrix(, nrow = dim(combn(nvars, ncausers))[[2]]*patinajnumber, ncol = nvars - ncausers - ndependents)   
for (i in as.integer(1:((dim(combn(nvars, ncausers))[[2]])*patinajnumber))){    
others[i, ]  <- setdiff(seq(1:nvars), independentsdependents[i,])   
}  
causalitiestemplate <- cbind(independentsdependents, others)  
causalitiestemplate  
}

以下是 DESCRIPTION FILE：

的内容

Package: causfinder  
Type: Package  
Title: A visual analyser for pairwise and multivariate conditional and partial  
Granger causalities. For a list of documented functions, use library(help =  
"causfinder")  
Version: 2.0  
Date: 2014-10-05  
Author: Erdogan CEVHER <erdogancevher@gmail.com>  
Maintainer: Erdogan CEVHER <erdogancevher@gmail.com>  
Description: Given a system of finite number of variables with their data in a  
matrix, the functions in the causfinder package analyze the pairwise and  
multivariate conditional and partial Granger causalities in a systematic  
and overall approach. By "overall approach" we mean that all the  
G-causalities among the variables in a certain desired pattern are  
calculated (the user then can retrieve his/her G-causality in interest as  
one element of the pattern). This pattern may correspond to pairwise or  
multivariate Granger causalities. Some of the functions in the package use  
bootstrapping whereas some others not. The analysis of the Granger  
causalities are performed via various ways; i.e., presenting the F  
statistics, p values, lower bounds and upper bounds of the bootstrapping  
values etc., and via presenting various plots and grid matrixes. For a list  
of documented functions, use library(help = "causfinder")  
Depends:  
    R (>= 3.0.2)  
Imports:  
    np(>= 0.50-1),RColorBrewer(>= 1.0-5),grid,scales(>= 0.2.4),boot(>= 1.3-11),calibrate(>= 1.7.2),combinat(>= 0.0-8),corpcor(>= 1.6.6)  
License: GPL (>= 3)  
LazyLoad: yes  
LazyData: yes  
URL: https://github.com/erdogancevher/causfinder

注意：将combinat包的函数combn重命名为combnnn并将其内容（.R文件等）放入我的包R文件夹中;并应用rexoginzation程序可能不会导致上述警告。我试图获得的只是一种系统的方法来防止警告，而不是我在本笔记中描述的非常棘手/漫长的方式。

Answer 1

如果路径上部的对象（遮蔽你真正想要的对象的对象）是你可以不用的东西，你可以使用命令

rm(object_name)

做的时候：

需要（ISLR）

我收到消息：

The following object is masked _by_ ‘.GlobalEnv’

所以通过做

来解决

rm(Auto)

我现在从ISLR包而不是GlobalEnv

引用Auto

如何防止＆＃34;以下对象被'package：...'掩盖：...＆＃34;装箱时遇到麻烦/警告？

1 个答案: