如何用corstarsl（）函数实现干净的相关表输出？

Question

有一个很好的相关表函数around（我知道的唯一一个对眼睛产生这种特殊的熟悉度）。 Bertold已经修改了代码以获得更好的输出。但是，有情况e。 G。当输出看起来有些混乱时，w /负相关。

在下面我首先显示函数，并在最小的示例下面显示：

corstarsl <- function(x){
  # corstars1() computes a correlation matrix w/ significance stars
  require(Hmisc)
  x <- as.matrix(x)
  R <- rcorr(x)$r
  p <- rcorr(x)$P

  ## define significance levels
  mystars <- ifelse(p < .001, "***", 
                    ifelse(p < .01, "** ", 
                           ifelse(p < .05, "* ", " ")))

  ## correlation matrix w/ two digits
  R <- format(round(cbind(rep(- 1.11, ncol(x)), R), 2))[, -1]

  ## build a new matrix that includes the correlations w/ appropriate stars
  Rnew <- matrix(paste(R, mystars, sep = ""), ncol = ncol(x))
  diag(Rnew) <- paste(diag(R), " ", sep = "")
  rownames(Rnew) <- colnames(x)
  colnames(Rnew) <- paste(colnames(x), "", sep = "")

  ## remove upper triangle
  Rnew <- as.matrix(Rnew)
  Rnew[upper.tri(Rnew, diag = TRUE)] <- ""
  Rnew <- as.data.frame(Rnew)

  ## remove last column and return the matrix (which is now a data frame)
  Rnew <- cbind(Rnew[1:length(Rnew) - 1])
  return(Rnew)
}

例：

library(MASS)
n <- 100
mymeans <- c(10, 12, 15, 17) # means of each var
Sigma <- matrix(c(1, -.45, .16, -.71,
                  -.45, 1, -.71, .09,
                  .16, -.71, 1, -.17,
                  -.71, .09, -.17, 1), ncol = 4)
dat <- mvrnorm(n = n, mu = mymeans, Sigma, empirical = TRUE)

(cortab <- corstarsl(as.data.frame(dat)))
##          V1       V2     V3
## V1                         
## V2 -0.45***                
## V3    0.16  -0.71***       
## V4 -0.71***    0.09  -0.17 

# or with htmlTable():
library(htmlTable)
htmlTable(cortab, 
      align = paste(rep('l', ncol(cortab)), collapse = ''))

输出中断：

编辑：左对齐我几乎就在那里，但如何给正值更多空间？

预期产量：

有谁知道如何在函数内实现更好的结果格式化（小数点应该对齐）？