Top left: Evolution of coefficients wk,t over time as the risk-factor model is fitted to cumulative case-counts yt,r normalized by county populations. - Cosmin Safta (11105442) (2025)
Results are plotted for the intercept and four principal components (PC). Only the intercept survives and is far larger that the weights associated with the principal components. Top right: Plot of the prediction error from a 7-fold cross-validation performed with the risk-factor model and LASSO, on case-count data accumulated over the entire two-and-a-half-year duration (and normalized by county populations). The figures on the upper horizontal axis denotes the number of principal components retained in the fitted model. and are clearly marked. Bottom left: Distribution of coefficients, corresponding to penalties and ; the intercept dominates. Bottom right: The residuals from the risk-factors model i.e., the component not explained by the risk-factors model. The spatial correlations are clear.