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The promise of multi-wavelength astronomy has been tempered by the largedisparity in sensitivity and resolution between different wavelength regimes.Here we present a statistical approach which attempts to overcome this byfitting parametric models directly to image data. Specifically, we fit a modelfor the radio luminosity function (LF) of star-forming galaxies to pixelintensity distributions at 1.4 GHz coincident with near-IR selected sources inCOSMOS. Taking a mass-limited sample in redshift bins across the range $0<z<4$we are able to fit the radio LF with ~0.2 dex precision in the key parameters(e.g. Phi*,L*). Good agreement is seen between our results and those usingstandard methods at radio and other wavelengths. Integrating our luminosityfunctions to get the star formation rate density we find that galaxies with astellar mass greater than $10^{9.5}\,$M$_{\odot}$ contribute at least 50 percent of cosmic star formation at since $z=4$. The scalability of our approachis empirically estimated, with the precision in LF parameter estimates found toscale with the number of sources in the stack as $\sqrt{N}$. This type ofapproach will be invaluable in the multi-wavelength analysis of upcomingsurveys with the SKA pathfinder facilities; LOFAR, ASKAP and MeerKAT.

Cosmic star formation probed via parametric stack-fitting of known sources to radio imaging