source('../../Data/data_loaders.R')

CXY = load_appendix_refinery_correlation_data()
N = 36 # number of observations
m = 10 # number of predictors

# Split the correlation matrix into its parts:
#
XTX = CXY[1:m, 1:m] # X^T X
XTy = CXY[1:m, m+1] # X^T y

# The VIFs:
#
print('VIFs')
VIFs = diag(solve(XTX))
print(VIFs)

# The eigenvalues:
#
ES = eigen(XTX)
print('Eigenvalues')
print(ES$values)

# The correlation between predictors:
#
print(XTX) # notice no r_ij > 0.95