  For noisy two-dimensional data, which are approximately uniformly distributed
near the circumference of an ellipse, Mardia and Holmes (1980) developed a
model to fit the ellipse. In this paper we adapt their methodology to the
analysis of helix data in three dimensions. If the helix axis is known, then
the Mardia-Holmes model for the circular case can be fitted after projecting
the helix data onto the plane normal to the helix axis. If the axis is unknown,
an iterative algorithm has been developed to estimate the axis. The methodology
is illustrated using simulated protein alpha-helices. We also give a
multivariate version of the Mardia-Holmes model which will be applicable for
fitting an ellipsoid and in particular a cylinder.
