# R/cor_sig.R In fastStat: Faster for Statistic Work

#### Documented in cor_sig

```#' Correlation Analysis with Signicant Values
#'
#' @param data a dataframe or matrix
#' @param method a character string indicating which correlation coefficient (or covariance) is to be computed. One of "pearson" (default), "kendall", or "spearman": can be abbreviated.
#'
#' @return correlation analysis with significant star.
#' @export
#'
#' @examples
#' cor_sig(mtcars)
cor_sig<- function(data,method="pearson") {
if (method==1) method='pearson'
if (method==2) method='kendall'
if (method==3) method='spearman'
message('')
message(method,' method')
res.cor = round(cor(data),3)
for (i in 1:(nrow(res.cor)-1)) {
for (j in (i+1):nrow(res.cor)) {
sig = as.numeric(cor.test(data[,rownames(res.cor)[i]],
data[,rownames(res.cor)[j]],
method=method)\$p.value)
res.cor[i,j]=round(sig,3)
}
res.cor[(i+1):nrow(res.cor),i]=''
}
for (i in 1:nrow(res.cor)) {
res.cor[i,i]=rownames(res.cor)[i]
}
message('')
message('***: p      <=0.001')
message(' **: p 0.01 ~ 0.001')
message('  *: p 0.05 ~ 0.01')
message('')
rownames(res.cor)=NULL
colnames(res.cor)[1]=' '
as.data.frame(res.cor)
}
```

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fastStat documentation built on Jan. 13, 2021, 7:32 a.m.