  Data gaps are ubiquitous in spectral irradiance data, and yet, little effort
has been put into finding robust methods for filling them. We introduce a
data-adaptive and nonparametric method that allows us to fill data gaps in
multi-wavelength or in multichannel records. This method, which is based on the
iterative singular value decomposition, uses the coherency between simultaneous
measurements at different wavelengths (or between different proxies) to fill
the missing data in a self-consistent way. The interpolation is improved by
handling different time scales separately.
  Two major assets of this method are its simplicity, with few tuneable
parameters, and its robustness. Two examples of missing data are given: one
from solar EUV observations, and one from solar proxy data. The method is also
appropriate for building a composite out of partly overlapping records.
