Estimates of functional Principal Component scores through PACE
Function scoresPACE
estimates the functional Principal Component
scores through Conditional Expectation (PACE)
scoresPACE(data, time, covestimate, PC)
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. |
covestimate |
a list with the two named entries "cov.estimate" and "meanfd" |
PC |
an object of class "pca.fd" |
a matrix of scores with dimension nrow = nharm and ncol = ncol(data)
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