Regression Equations, Generalized Least Squares, Correlation Matrices, Python, Statsmodels.
We’ll assume that the regression errors for any individual model (or pair of models) are homoskedastic i.e. they demonstrate constant variance. i.e. for any ϵ_ti and ϵ_tj in Ω, (ϵ_ti)(ϵ_tj) = σ²_ij With these two assumptions in place, it can be shown that the covariance matrix of errors Ω can be