Lancaster EPrints

spatsurv:an R package for Bayesian inference with spatial survival models

Taylor, Benjamin and Rowlingson, Barry (2017) spatsurv:an R package for Bayesian inference with spatial survival models. Journal of Statistical Software, 77 (4). pp. 1-32.

PDF (spatsurv) - Submitted Version
Available under License Creative Commons Attribution.

Download (937Kb) | Preview


    Survival methods are used for the statistical modelling of time-to-event data, with applications in many scientific fields. Survival data are characterised by a set of complete records, in which the time of the event is known; and a set of censored records, in which the event was known to have occurred in an interval. When survival data are spatially referenced, the spatial variation in survival times may be of scientific interest. In this article, we introduce a new R package, spatsurv, for inference with spatially referenced survival data. The specific type of model fitted by this package is a parametric proportional hazards model in which the spatially correlated frailties are modelled by a log-Gaussian stochastic process. The package is extensible in that it allows the user to easily create new models for the baseline hazard function and spatial covariance function. The package implements an advanced adaptive Markov chain Monte Carlo algorithm to deliver Bayesian inference with minimal input from the user.

    Item Type: Journal Article
    Journal or Publication Title: Journal of Statistical Software
    Departments: Faculty of Health and Medicine > Medicine
    ID Code: 78132
    Deposited By: ep_importer_pure
    Deposited On: 05 Feb 2016 13:30
    Refereed?: Yes
    Published?: Published
    Last Modified: 29 Apr 2019 15:43
    Identification Number:

    Actions (login required)

    View Item