estimate_SHUM: Smooth Approximations Of Empirical Hyper Volume Under...

In SCOR: Spherically Constrained Optimization Routine

Smooth Approximations Of Empirical Hyper Volume Under Manifolds

Description

'SHUM' is a class of smoothed estimates of EHUM.

Usage

estimate_SHUM(beta, labels, x_mat, p = 0)

Arguments

beta	The parameter we measure SHUM based on.
labels	The labels of the Columns of the data matrix.
x_mat	The Data Matrix
p	p decides whether to use s_n(x) or \phi_n(x). p = 1 stands for \phi_n(x) and p = 0 stands for s_n(x)

Value

Smooth approximation of the empirical Hyper-volume Under Manifolds Estimate

References

• Maiti, Raju and Li, Jialiang and Das, Priyam and Feng, Lei and Hausenloy, Derek and Chakraborty, Bibhas
  "A distribution-free smoothed combination method of biomarkers to improve diagnostic accuracy in multi-category classification"
  (available at 'arXiv https://arxiv.org/abs/1904.10046).

Examples

estimate_SHUM(rep(1, 12), colnames(AL), AL)
estimate_SHUM(rep(1, 12), colnames(AL), AL, p = 1)


estimate_SHUM(1:10 , sample(c( rep("lab1", 10), rep("lab2", 10), rep("lab3", 10))),
matrix(rnorm(300), nrow = 10))

SCOR documentation built on July 9, 2023, 6:39 p.m.