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scoresPACE

Estimates of functional Principal Component scores through PACE


Description

Function scoresPACE estimates the functional Principal Component scores through Conditional Expectation (PACE)

Usage

scoresPACE(data, time, covestimate, PC)

Arguments

data

a matrix object or list – If the set is supplied as a matrix object, the rows must correspond to argument values and columns to replications, and it will be assumed that there is only one variable per observation. If y is a three-dimensional array, the first dimension corresponds to argument values, the second to replications, and the third to variables within replications. – If it is a list, each element must be a matrix object, the rows correspond to argument values per individual. First column corresponds to time points and following columns to argument values per variable.

time

Array with time points where data was taken. length(time) == dim(data)[1]

covestimate

a list with the two named entries "cov.estimate" and "meanfd"

PC

an object of class "pca.fd"

Value

a matrix of scores with dimension nrow = nharm and ncol = ncol(data)


fda

Functional Data Analysis

v5.1.9
GPL (>= 2)
Authors
J. O. Ramsay <ramsay@psych.mcgill.ca> [aut,cre], Spencer Graves <spencer.graves@effectivedefense.org> [ctb], Giles Hooker <gjh27@cornell.edu> [ctb]
Initial release
2020-12-16

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