  In numerous graph signal processing applications, data is often missing for a
variety of reasons, and predicting the missing data is essential. In this
paper, we consider data on graphs modeled as bandlimited graph signals.
Predicting or reconstructing the unknown signal values for such a model
requires an estimate of the signal bandwidth. In this paper, we address the
problem of estimating the reconstruction errors, minimizing which would thereby
provide an estimate of the signal bandwidth. In doing so, we design a
cross-validation approach needed for stable graph signal reconstruction and
propose a method for estimating the reconstruction errors for different choices
of signal bandwidth. Using this technique, we are able to estimate the
reconstruction error on a variety of real-world graphs.
