source('../../Data/data_loaders.R') DF = load_appendix_pitprop_data() N = 180 # number of samples m = 13 # number of measurements # Extract the coefficients of the linear model: # As we have a correlation matrix these predictors are centered and normalized (divided by the standard deviation) ' # XTy = as.matrix( DF[1:m, m+1] ) XTX = as.matrix( DF[1:m, 1:m] ) beta_hat = solve( XTX, XTy )