computeMu: Compute mu

In morpheus: Estimate Parameters of Mixtures of Logistic Regressions

Compute mu

Description

Estimate the normalized columns mu of the beta matrix parameter in a mixture of logistic regressions models, with a spectral method described in the package vignette.

Usage

computeMu(X, Y, optargs = list())

Arguments

X	Matrix of input data (size nxd)
Y	Vector of binary outputs (size n)
optargs	List of optional argument: 'jd_method', joint diagonalization method from the package jointDiag: 'uwedge' (default) or 'jedi'. 'jd_nvects', number of random vectors for joint-diagonalization (or 0 for p=d, canonical basis by default) 'M', moments of order 1,2,3: will be computed if not provided. 'K', number of populations (estimated with rank of M2 if not given)

Value

The estimated normalized parameters as columns of a matrix mu of size dxK

See Also

multiRun to estimate statistics based on mu, and generateSampleIO for I/O random generation.

Examples

io <- generateSampleIO(10000, 1/2, matrix(c(1,0,0,1),ncol=2), c(0,0), "probit")
mu <- computeMu(io$X, io$Y, list(K=2)) #or just X and Y for estimated K

morpheus documentation built on Feb. 16, 2023, 10:01 p.m.