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Regardless of whether or not all fast radio bursts (FRBs) repeat, those thatdo form a population with a distribution of rates. This work considers apower-law model of this population, with rate distribution $\Phi_r \simR^{\gamma_r}$ between $R_{\rm min}$ and $R_{\rm max}$. The zDM code is used tomodel the probability of detecting this population as either apparentlyonce-off or repeat events as a function of redshift, $z$, and dispersionmeasure, DM. I demonstrate that in the nearby Universe, repeating sources cancontribute significantly to the total burst rate. This causes an apparentdeficit in the total number of observed sources (once-off and repeaters)relative to the distant Universe that will cause a bias in FRB populationmodels. Thus instruments with long exposure times should explicitly takerepetition into account when fitting the FRB population.  I then fit data from The Canadian Hydrogen Intensity Mapping Experiment(CHIME). The relative number of repeat and apparently once-off FRBs, and theirDM, declination, and burst rate distributions, can be well-explained by50--100\% of CHIME single FRBs being due to repeaters, with $R_{\rm max} >0.75$ day$^{-1}$ above $10^{39}$ erg, and ${\gamma_r} = -2.2_{-0.8}^{+0.6}$.This result is surprisingly consistent with follow-up studies of FRBs detectedby the Australian Square Kilometre Array Pathfinder (ASKAP). Thus the evidencesuggests that CHIME and ASKAP view the same repeating FRB population, which isresponsible not just for repeating FRBs, but the majority of apparentlyonce-off bursts.  For greater quantitative accuracy, non-Poissonian arrival times, second-ordereffects in the CHIME response, and a simultaneous fit to the total FRBpopulation parameters, should be treated in more detail in future studies.

Modelling repetition in zDM: a single population of repeating fast radio bursts can explain CHIME data