logit.envMU: Estimate the envelope subspace in logistic regression

Description Usage Arguments Details Value References

View source: R/logit.envMU.R

Description

Estimate the envelope subspace with specified dimension in logistic regression.

Usage

1
logit.envMU(X, Y, u)

Arguments

X

Predictors. An n by p matrix, p is the number of predictors. The predictors can be univariate or multivariate, discrete or continuous.

Y

Response. An n by 1 matrix. The univariate response must be binary.

u

Dimension of the envelope. An integer between 0 and p.

Details

This function estimate the envelope subspace in logistic regression using an non-Grassmann optimization algorithm. The starting value and optimization algorithm is described in Cook et al. (2016).

Value

Gammahat

The orthonormal basis of the envelope subspace.

Gamma0hat

The orthonormal basis of the complement of the envelope subspace.

muhat

The estimated intercept of the canonical parameter.

etahat

The estimated beta of the canonical parameter with respect to Gamma.

weighthat

The estimated weight defined as C"(theta) / E(C"(theta)) where C(theta) is the conditional log likelihood.

Vhat

The estimated V defined as V = theta + (Y - mu (theta) / W).

avar

The asympotic covariance of vec(beta).

objfun

The minimized objective function.

References

Cook, R. D., Forzani, L. and Su, Z. (2016) A Note on Fast Envelope Estimation. Journal of Multivariate Analysis. 150, 42-54.


Renvlp documentation built on Feb. 28, 2019, 1:04 a.m.