correlate: Function to compute various correlation measures between two...
In bhklab/mRMRe: Parallelized Minimum Redundancy, Maximum Relevance (mRMR)

Description Usage Arguments Details Value Author(s) See Also Examples

Correlate is a function that cestimates correlation between two variables, which can be either continuous, categorical (ordered factor) or censored (survival data).

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correlate(X, Y, method = c("pearson", "spearman", "kendall", "frequency", "cramersv",
		"cindex"),strata, weights, outX = TRUE, bootstrap_count = 0, alpha = 0.05,
 		alternative = c("two.sided", "less", "greater"))

`X`	Vector of type numeric, ordered factor, or Surv.
`Y`	Vector of type numeric, ordered factor, or Surv of same length as `X`.
`method`	One of the following values: pearson, spearman, kendall, frequency, cramersv, or cindex.
`strata`	Vector of type factor corresponding to the sample strata.
`weights`	Vector of type numeric corresponding to the sample weights.
`outX`	For cindex, if set to `TRUE`, ignore ties; otherwise, take them into account when computing the concordance index.
`bootstrap_count`	If set to `0`, analytical standard error for the correlation estimate in each strata is used to compute the meta-estimate (inverse-variance weighting avarega); otherwise a number of bootstraps are used to computes standard errors.
`alpha`	The probability of Type I error that is, rejecting a null hypothesis when it is in fact true
`alternative`	a character string specifying the alternative hypothesis,must be one of two.sided (default), greater or less. You can specify just the initial letter.

The correlate function could be used to measure correlation between any types of variables:

numeric vs. numeric: Pearson, Spearman, Kendall or concordance index
numeric vs. ordered factor: concordance index (Somers' Dxy)
numeric vs. survival data: concordance index (Somers' Dxy)
ordered factor vs. ordered factor: Carmer's V
ordered factor vs. survival data: concordance index (Somers' Dxy)
survival data vs. survival data: concordance index (Somers' Dxy)

Part of the code underlying correlate is also used in mim method of the mRMRe.Data object because correlations are used to build the mutual information matrix in order for feature selection to take place. This is why these two functions have many argiuments in common.

`estimate`	point estimate
`se`	standard error
`lower`	lower confidence bound
`upper`	upper confidence bound
`p`	p-value
`n`	sample size

Nicolas De Jay, Simon Papillon-Cavanagh, Benjamin Haibe-Kains

mRMRe.Data-class

set.thread.count(2)

## load data
data(cgps)
   
## spearman correlation coefficent between the first gene and Camptothecin IC50
correlate(X=cgps.ge[ ,1], Y=cgps.ic50, method="spearman")
   
## concordance index between the first gene and Camptothecin IC50
correlate(X=cgps.ge[ ,1], Y=cgps.ic50, method="cindex")