Summary Statistics

Of all the metrics output in a metrics.json file, the Summary Statistics for a calibration run the most risk of being misinterpreted. Always keep in mind that these figures represent broad mathematical strokes, and should be interpreted holistically along with the rest of the metrics of a calibration.

Per-Component RMSE

Per-Component RMSE stands for the Root Mean Square of the Error, which in this case is the residuals for all observations related to a single component. For a component that has been appropriately modeled (i.e. there are no un-modeled systematic error sources present), this represents the mean quantity of error from observations taken by a single component.

Units

Units for RMSE are specific to the component in question, and should not necessarily be compared directly. For example, camera components will be making observations in units of pixels in image space, which means our RMSE is in units of pixels as well.

!!! warning "Comparing Camera RMSE" If two cameras have pixels of different sizes, then it is important to first convert these RMSEs to some metric size so as to compare them equally. This is what pixel_pitch in the Plex API is for, so that cameras can be compared more equally (as the pixel size between two cameras is not always equal!).

Posterior Variance

Sometimes referred to more completely as the "a-posteriori variance factor" or "normalized cost," the posterior variance is a relative measure of the gain/loss of information from the calibration.

!!! info "Advanced Topic: Posterior Variance" Posterior variance is often misunderstood (partly because the topic is unfamiliar outside of Bayesian statistical methods). Learn more about this number and what it entails in the Advanced Topics for TVCal.