weighted.Deville: Perform a weighted PCA using Deville's method on a data...

In DrBats: Data Representation: Bayesian Approach That's Sparse

Perform a weighted PCA using Deville's method on a data matrix X that we project onto a histogram basis and weighted

Description

Perform a weighted PCA using Deville's method on a data matrix X that we project onto a histogram basis and weighted

Usage

weighted.Deville(X, t, t.range, breaks, Qp = NULL)

Arguments

X	a data matrix
t	a matrix of observation times corresponding to X
t.range	the range of observation times in vector form (ex. t.range = c(a, b))
breaks	integer number of histogram windows
Qp	a matrix of weights, if Qp = NULL the function specifies a diagonal weight matrix

Value

X.histo the matrix projected onto the histogram basis

U.histo a matrix of eigenvectors in the histogram basis

Cp a matrix of principal components

lambda a vector of eigenvalues

perc.lambda a vector of the percentage of total inertia explained by each principal component

Author(s)

Gabrielle Weinrott

Examples

res <- drbats.simul(N = 5, P = 100, t.range = c(5, 100), breaks = 8)
res.weighted <- weighted.Deville(res$X, res$t.simul, t.range = c(5, 100), breaks = 8, Qp = NULL)
res.weighted

DrBats documentation built on March 18, 2022, 5:15 p.m.