Package: timedelay
Version: 1.0.11
Date: 2020-05-18
Title: Time Delay Estimation for Stochastic Time Series of
        Gravitationally Lensed Quasars
Author: Hyungsuk Tak, Kaisey Mandel, David A. van Dyk, Vinay L.
        Kashyap, Xiao-Li Meng, Aneta Siemiginowska, and Zhirui Hu
Maintainer: Hyungsuk Tak <hyungsuk.tak@gmail.com>
Depends: R (>= 3.5.0)
Imports: MASS (>= 7.3-51.3), mvtnorm(>= 1.0-11)
Description: 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>.
License: GPL-2
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-06-19 10:41:41 UTC; root
Repository: https://hyungsuktak.r-universe.dev
Date/Publication: 2020-05-19 10:50:02 UTC
RemoteUrl: https://github.com/cran/timedelay
RemoteRef: HEAD
RemoteSha: 9a87917b580e40ab2085d3178561da55248a97a0