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Perform a weighted PCA using Deville's method on a data matrix X that we project onto a histogram basis and weighted
weighted.Deville(X, t, t.range, breaks, Qp = NULL)
a data matrix
a matrix of observation times corresponding to X
the range of observation times in vector form (ex. t.range = c(a, b))
integer number of histogram windows
a matrix of weights, if Qp = NULL the function specifies a diagonal weight matrix
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
# NOT RUN { 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 # }
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