  We present analytical reconstructions of type Ia supernova (SN Ia) delay time
distributions (DTDs) by way of two independent methods: by a Markov chain Monte
Carlo best-fit technique comparing the volumetric SN Ia rate history to today's
compendium cosmic star-formation history, and secondly through a maximum
likelihood analysis of the star formation rate histories of individual galaxies
in the GOODS/CANDELS field, in comparison to their resultant SN Ia yields. We
adopt a flexible skew-normal DTD model, which could match a wide range of
physically motivated DTD forms. We find a family of solutions that are
essentially exponential DTDs, similar in shape to the $\beta\approx-1$
power-law DTDs, but with more delayed events (>1 Gyr in age) than prompt events
(<1 Gyr). Comparing these solutions to delay time measures separately derived
from field galaxies and galaxy clusters, we find the skew-normal solutions can
accommodate both without requiring a different DTD form in different
environments. These model fits are generally inconsistent with results from
single-degenerate binary population synthesis models, and are seemingly
supportive of double-degenerate progenitors for most SN Ia events.
