hhat: Regularizing h function

In martinoandrea92/dpdistance: Inference and Clustering of Functional Data

Description

This function computes the values of the regularizing function for the generalized Mahalanobis distance.

Usage

hhat(p, lambda)

Arguments

p	a positive numeric value containing the parameter of the regularizing function for the generalized Mahalanobis distance.
lambda	a vector containing the eigenvalues of the covariance matrix of the functional data from which "x" and "y" are extracted.

Value

The function returns a vector of the values of the regularizing function for the generalized Mahalanobis distance.

Examples

# Define the parameters of the function
p <- 10^3
K <- 150
lambda <- rep( 0, K )
for ( k in 1:K ) {
  lambda[k] <- 1 / ( k + 1 )^2
}

h <- hhat( p, lambda )

martinoandrea92/dpdistance documentation built on May 29, 2019, 3:44 a.m.