The R-squared and adjusted R-squared values shown in Table \ref{table:results_high_dimensional_model} would suggest that a reasonable classification fit has been achieved with this model across the 20 technology profiles considered during the emergence phase. Specifically, this suggests a good level of accuracy based on the classification residuals, whilst the F-ratio of 5.60 with degrees of freedom 7.78 and 11.22 respectively implies that the relationship established has a p-value somewhere between 0.0041 and 0.0060. As such this result appears to be significant at the 1% level, meaning that is unlikely that this classification label set would occur by chance.
However, to ensure that this is the most appropriate fit to the data presented, the high-dimensional model initially developed was subsequently benchmarked against a low-dimensional model (i.e. when the beta basis system for each regression coefficient is made up of a small number of B-splines), as well as a constant and a monomial based model. The corresponding 'goodness-of-fit' measures for the alternative functional linear regression models are compiled in Table \ref{table:results_benchmarking}.