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hierSDR (version 0.1)

phd: 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