  We develop a density ridge search algorithm based on a novel density ridge
definition. This definition is based on a conditional variance matrix and the
mode in the lower dimensional subspace. It is compared to the subspace
constraint mean shift algorithm, based on the gradient and Hessian of the
underlying probability density function. We show the advantages of the new
algorithm in a simulation study and estimate galaxy filaments from a data set
of the Baryon Oscillation Spectroscopic Survey.
