phd {hierSDR}

PHD SDR fitting function

Description

fits SDR models (PHD approach)

Usage

phd(x, y, d = 5L)

Arguments

x

an n x p matrix of covariates, where each row is an observation and each column is a predictor

y

vector of responses of length n

d

an integer representing the structural dimension

Value

A list with the following elements

• beta.hat estimated sufficient dimension reduction matrix

• eta.hat coefficients on the scale of the scaled covariates

• cov variance covariance matric for the covariates

• sqrt.inv.cov inverse square root of the variance covariance matrix for the covariates. Used for scaling

• M matrix from principal Hessian directions

• eigenvalues eigenvalues of the M matrix