I would like to do this:
fit <- test( measured_values, fitted_values )
- the return value from the
testfunction is: 0 < fit < 1.
- measured_values are the observed data.
- fitted_values are the data for the curve produced by GAM for the measured_values.
What test can I use to compare the data sets that will result in a number between 0 and 1, where 0 indicates the measured values and the fitted values are not a good fit and 1 indicates the fitted values fit perfectly to the measured values?
For example, consider the data plotted here: http://i.imgur.com/cFLRN.jpg
The fit, produced by GAM, is fairly close to ideal. However, the standard correlations (shown in the bottom left) do not accurately indicate the goodness of fit.