PyCCF emulates a Fortran program written by B. Peterson for use with reverberation mapping. The code cross correlates two light curves that are unevenly sampled using linear interpolation and measures the peak and centroid of the cross-correlation function. In addition, it is possible to run Monto Carlo iterations using flux randomization and random subset selection (RSS) to produce cross-correlation centroid distributions to estimate the uncertainties in the cross correlation results.

JAVELIN (formerly known as SPEAR) is an approach to reverberation mapping that computes the lags between the AGN continuum and emission line light curves and their statistical confidence limits. It uses a damped random walk model to describe the quasar continuum variability and the ansatz that emission line variability is a scaled, smoothed and displaced version of the continuum. While currently configured only to simultaneously fit light curve means, it includes a general linear parameters formalism to fit more complex trends or calibration offsets. The noise matrix can be modified to allow for correlated errors, and the correlation matrix can be modified to use a different stochastic process. The transfer function model is presently a tophat, but this can be altered by changing the line-continuum covariance matrices. It is also able to cope with some problems in traditional reverberation mapping, such as irregular sampling, correlated errors and seasonal gaps.