  Modern developments in microscopy and image processing are revolutionising
areas of physics, chemistry, and biology as nanoscale objects can be tracked
with unprecedented accuracy. However, the price paid for having a direct
visualisation of a single particle trajectory with high temporal and spatial
resolution is a consequent lack of statistics. This naturally calls for
reliable analytical tools which will allow one to extract the properties
specific to a statistical ensemble from just a single trajectory. In this
article we briefly survey different analytical methods currently used to
determine the ensemble average diffusion coefficient from single particle data
and then focus specifically on weighted least-squares estimators, seeking the
weight functions for which such estimators are ergodic. Finally, we address the
question of the effects of disorder on such estimators.
