minerva (version 1.5.10)

cstats: 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].

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

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

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).

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.

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).

Examples

# NOT RUN {
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)

# }