Nothing
## ---- echo = FALSE, message = FALSE, warning = FALSE---------------------
require(intercure)
## ---- eval = FALSE-------------------------------------------------------
# sim_bch(10)
## ---- echo = FALSE-------------------------------------------------------
set.seed(2)
knitr::kable(sim_bch(10), align = 'c')
## ---- message = FALSE, warning = FALSE, results = 'hide'-----------------
# hypothetical interval censored dataset with a cure fraction
set.seed(2)
cureset <- sim_bch(100)
# allocates the estimated parameters and covariance matrix
output <- inter_bch(cureset,
cureset$L, cureset$R,
c("xi1", "xi2"))
## ------------------------------------------------------------------------
output$par
## ------------------------------------------------------------------------
indiv <- c(1, 1, 0)
est_effect <- output$par
cf <- exp(-exp(est_effect[1:3]%*%indiv))
cf
## ---- eval = FALSE-------------------------------------------------------
# sim_frailty(10)
## ---- echo = FALSE-------------------------------------------------------
set.seed(3)
knitr::kable(sim_frailty(10), align = 'c')
## ---- message = FALSE, warning = FALSE, results = 'hide'-----------------
# hypothetical interval censored dataset with a cure fraction
set.seed(2)
cureset <- sim_frailty(100)
# allocates the estimated parameters and covariance matrix
output <- inter_frailty(cureset,
cureset$L, cureset$R, cureset$delta,
c("xi1", "xi2"), c("xi1", "xi2"),
M = 10, max_n = 30, burn_in = 10)
## ------------------------------------------------------------------------
output$par
## ------------------------------------------------------------------------
indiv <- c(1, 1, 0)
est_effect <- output$par
cf <- exp(-exp(est_effect[1:3]%*%indiv)/2)
cf
## ---- eval = FALSE-------------------------------------------------------
# require(parallel)
# require(doParallel)
# cl <- makeCluster(4)
# registerDoParallel(cl)
# output <- inter_frailty(cureset,
# cureset$L, cureset$R, cureset$delta,
# c("xi1", "xi2"), c("xi1", "xi2"),
# M = 10, par_cl = cl)
#
#
#
# stopCluster(cl)
## ---- eval = FALSE-------------------------------------------------------
# sim_frailty_cl(15, nclus = 3)
## ---- echo = FALSE-------------------------------------------------------
set.seed(2)
knitr::kable(sim_frailty_cl(15, nclus = 3), align = 'c')
## ---- message = FALSE, warning = FALSE, results = 'hide'-----------------
# hypothetical interval censored dataset with a cure fraction
set.seed(2)
cureset <- sim_frailty_cl(120, nclus = 3)
# allocates the estimated parameters and covariance matrix
output <- inter_frailty_cl(cureset,
cureset$L, cureset$R, cureset$delta,
c("xi1", "xi2"), c("xi1", "xi2"),
grp = cureset$clus, M = 30, max_n = 30,
burn_in = 10)
## ------------------------------------------------------------------------
output$par
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