Fit linear regression model based on the principal components scores for each patent indicator data object
Extract functional principal component analysis coefficients for building linear regression model and determine the variance of coefficients
Combine the fPCA coefficients with the corresponding fPCA harmonic function for each patent indicator data object
Combine the fPCA coefficient variances with the square of the corresponding fPCA harmonic function for each patent indicator data object