## File: cstats.Rd

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 12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152 % Generated by roxygen2: do not edit by hand % Please edit documentation in R/RcppExports.R \name{cstats} \alias{cstats} \title{Compute statistics (MIC and normalized TIC) between each pair of the two collections of variables (convenience function). If n and m are the number of variables in X and Y respectively, then the statistic between the (row) i (for X) and j (for Y) is stored in \code{mic[i, j]} and \code{tic[i, j]}.} \usage{ cstats(x, y, alpha = 0.6, C = 15, est = "mic_approx") } \arguments{ \item{x}{Numeric Matrix of m-by-n with n variables and m samples.} \item{y}{Numeric Matrix of m-by-p with p variables and m samples.} \item{alpha}{number (0, 1.0] or >=4 if alpha is in (0,1] then B will be max(n^alpha, 4) where n is the number of samples. If alpha is >=4 then alpha defines directly the B parameter. If alpha is higher than the number of samples (n) it will be limited to be n, so B = min(alpha, n).} \item{C}{number (> 0) determines how many more clumps there will be than columns in every partition. Default value is 15, meaning that when trying to draw x grid lines on the x-axis, the algorithm will start with at most 15*x clumps.} \item{est}{string ("mic_approx", "mic_e") estimator. With est="mic_approx" the original MINE statistics will be computed, with est="mic_e" the equicharacteristic matrix is is evaluated and MIC_e and TIC_e are returned.} } \value{ list of two elements: MIC: the MIC statistic matrix (n x p). TIC: the normalized TIC statistic matrix (n x p). } \description{ Compute statistics (MIC and normalized TIC) between each pair of the two collections of variables (convenience function). If n and m are the number of variables in X and Y respectively, then the statistic between the (row) i (for X) and j (for Y) is stored in \code{mic[i, j]} and \code{tic[i, j]}. } \examples{ x <- matrix(rnorm(2560), ncol=8, nrow=320) y <- matrix(rnorm(1280), ncol=4, nrow=320) mictic <- cstats(x, y, alpha=9, C=5, est="mic_e") head(mictic) }