euclsq: Matrix of distances

In mlesnoff/rchemo: Dimension reduction, Regression and Discrimination for Chemometrics

Matrix of distances

Description

—– Matrix (n, m) of distances between row observations of two datasets X (n, p) and Y (m, p)

- euclsq: Squared Euclidean distance

- mahsq: Squared Mahalanobis distance

—– Matrix (n, 1) of distances between row observations of a dataset X (n, p) and a vector p (n)

- euclsq_mu: Squared Euclidean distance

- mahsq_mu: Squared Euclidean distance

Usage

euclsq(X, Y = NULL)

euclsq_mu(X, mu)

mahsq(X, Y = NULL, Uinv = NULL)

mahsq_mu(X, mu, Uinv = NULL)

Arguments

X	X-data (n, p).
Y	Data (m, p) compared to X. If NULL (default), Y is set equal to X.
mu	Vector (p) compared to X.
Uinv	For Mahalanobis distance. The inverse of a Choleski factorization matrix of the covariance matrix of X. If NULL (default), Uinv is calculated internally.

Value

A distance matrix.

Examples

n <- 5 ; p <- 3
X <- matrix(rnorm(n * p), ncol = p)

euclsq(X)
as.matrix(stats::dist(X)^2)
euclsq(X, X)

Y <- X[c(1, 3), ]
euclsq(X, Y)
euclsq_mu(X, Y[2, ])

i <- 3
euclsq(X, X[i, , drop = FALSE])
euclsq_mu(X, X[i, ])

S <- cov(X) * (n - 1) / n
i <- 3
mahsq(X)[i, , drop = FALSE]
stats::mahalanobis(X, X[i, ], S)

mahsq(X)
Y <- X[c(1, 3), ]
mahsq(X, Y)

mlesnoff/rchemo documentation built on April 15, 2023, 1:25 p.m.