# mine_compute_cstats: Compute statistics (MIC and normalized TIC) between each pair... In minerva: Maximal Information-Based Nonparametric Exploration for Variable Analysis

## 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 mic[i, j] and tic[i, j].

## Usage

 `1` ```mine_compute_cstats(x, y, alpha = 0.6, C = 15, est = "mic_approx") ```

## Arguments

 `x` Numeric Matrix of m-by-n with n variables and m samples. `y` Numeric Matrix of m-by-p with p variables and m samples. `alpha` float (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). `C` float (> 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. `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).

minerva documentation built on Dec. 14, 2018, 5:04 p.m.