postTheta

logpostDelta

postX

Log.post.theta

postTheta.multi

postBeta

Log.post.delta

postX.multi

orderData

<p>Internal <code>bayesian</code> functions</p>

internal

timedelay-internal

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 state-space representation for  irregularly observed time series data generated from a latent continuous-time Ornstein-Uhlenbeck process. Our Bayesian method adopts scientifically motivated hyper-prior distributions and a Metropolis-Hastings 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. A new functionality is added in version 1.0.9 for estimating the time delay between doubly-lensed light curves observed in two bands. See also Tak et al. (2017) <doi:10.1214/17-AOAS1027>, Tak et al. (2018) <doi:10.1080/10618600.2017.1415911>, Hu and Tak (2020) <arXiv:2005.08049>.

Hyungsuk Tak

timedelay

Time Delay Estimation for Stochastic Time Series of
Gravitationally Lensed Quasars

timedelay-internal function

Internal <code>bayesian</code> functions — timedelay-internal

Internal <code>bayesian</code> functions

timedelay-internal: Internal `bayesian` functions

Description

Arguments

Details