  We present a maximum likelihood method for fitting two-dimensional model
distributions to stellar data in colour-magnitude space. This allows one to
include (for example) binary stars in an isochronal population. The method also
allows one to derive formal uncertainties for fitted parameters, and assess the
likelihood that a good fit has been found. We use the method to derive an age
of 38.5 +3.5/-6.5 Myrs and a true distance modulus of 7.79 +0.11/-0.05 mags
from the V vs V-I diagram of NGC2547 (the uncertainties are 67 percent
confidence limits, and the parameters are insensitive to the assumed binary
fraction). These values are consistent with those previously determined from
low-mass isochronal fitting, and are the first measurements to have
statistically meaningful uncertainties. The age is also consistent with the
lithium depletion age of NGC2547, and the HIPPARCOS distance to the cluster is
consistent with our value.
  The method appears to be quite general and could be applied to any
N-dimensional dataset, with uncertainties in each dimension. However, it is
particularly useful when the data are sparse, in the sense that both the
typical uncertainties for a datapoint and the size of structure in the function
being fitted are small compared with the typical distance between datapoints.
In this case binning the data will lose resolution, whilst the method presented
here preserves it.
  Software implementing the methods described in this paper is available from
http://www.astro.ex.ac.uk/people/timn/tau-squared/.
