CoxWorker worker objectsCoxMaster.RdCoxMaster objects instantiate and run a distributed Cox model
computation fit
CoxWorker which generates objects matched to such a master object
new()CoxMaster objects instantiate and run a distributed Cox model
computation fit
CoxMaster$new(defn, debug = FALSE)
defna computation definition
debuga flag for debugging, default FALSE
R6 CoxMaster object
kosher()Check if inputs and state of object are sane. For future use
CoxMaster$kosher()
TRUE or FALSE
logLik()Return the partial log likelihood on all data for given beta parameter.
CoxMaster$logLik(beta)
betathe parameter vector
a named list with three components: value contains the value of the
log likelihood, gradient contains the score vector, and hessian contains
the estimated hessian matrix
addSite()Add a url or worker object for a site for participating in the distributed computation. The worker object can be used to avoid complications in debugging remote calls during prototyping.
CoxMaster$addSite(name, url = NULL, worker = NULL)
nameof the site
urlweb url of the site; exactly one of url or worker should be specified
workerworker object for the site; exactly one of url or worker should be specified
run()Run the distributed Cox model fit and return the estimates
CoxMaster$run(control = coxph.control())
controlparameters, same as survival::coxph.control()
a named list of beta, var, gradient, iter, and returnCode
#' @description ' Return the summary of fit as a data frame
summary()CoxMaster$summary()
a summary data frame columns for coef,
exp(coef), ' standard error, z-score, and p-value for each
parameter in the model following the same format as the
survival package
clone()The objects of this class are cloneable with this method.
CoxMaster$clone(deep = FALSE)
deepWhether to make a deep clone.