We provide a toolbox to estimate the time delay between the brightness time series of gravitationally lensed quasar images via Bayesian and profile likelihood approaches. The model is based on a statespace representation for irregularly observed time series data generated from a latent continuoustime OrnsteinUhlenbeck process. Our Bayesian method adopts scientifically motivated hyperprior distributions and a MetropolisHastings within Gibbs sampler, producing posterior samples of the model parameters that include the time delay. A profile likelihood of the time delay is a simple approximation to the marginal posterior distribution of the time delay. Both Bayesian and profile likelihood approaches complement each other, producing almost identical results; the Bayesian way is more principled but the profile likelihood is easier to implement.
Package details 


Author  Hyungsuk Tak, Kaisey Mandel, David A. van Dyk, Vinay L. Kashyap, XiaoLi Meng, and Aneta Siemiginowska 
Date of publication  20170527 21:23:42 UTC 
Maintainer  Hyungsuk Tak <hyungsuk.tak@gmail.com> 
License  GPL2 
Version  1.0.7 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.