Metrics for sign detection — count

Calculates sensitivity, specificity and precision for ternary data (with -1 for negative effect, 0 for no effect, 1 for positive effect).

Usage

count_vector(truth, estim)

count_matrix(truth, estim)

Arguments

truth: (i) vector of length \(p\) or (ii) \(n \times p\) matrix with entries in -1, 0, 1
estim: (i) vector of length \(p\) or (ii) \(p \times n\) matrix with entries -1, 0, 1

Value

Returns a vector of length 3 (with names "sensitivity", "specificity" and "precision") or a matrix with 3 rows (with names "sensitivity", "specificity" and "precision") and \(n\) columns.

Examples

#--- vector ---
p <- 20
truth <- sample(x=c(-1,0,1),size=p,replace=TRUE)
estim <- sample(x=c(-1,0,1),size=p,replace=TRUE)
table(truth,estim)
#>      estim
#> truth -1 0 1
#>    -1  0 1 5
#>    0   3 4 0
#>    1   4 3 0
count_vector(truth,estim)
#> sensitivity specificity   precision 
#>   0.0000000   0.5714286   0.0000000 

#--- matrix ---
p <- 20
n <- 5
truth <- matrix(sample(x=c(-1,0,1),size=n*p,replace=TRUE),nrow=p,ncol=n)
estim <- matrix(sample(x=c(-1,0,1),size=n*p,replace=TRUE),nrow=p,ncol=n)
count_matrix(truth,estim)
#>             [,1]      [,2]      [,3]  [,4]      [,5]
#> sensitivity  0.3 0.3076923 0.5454545 0.625 0.5454545
#> specificity  0.5 0.5714286 0.0000000 0.250 0.4444444
#> precision    0.3 0.4000000 0.3529412 0.625 0.4615385