cyclomort (version 1.0.2)

simulate_cycloSurv: Simulate periodic mortality process

Description

Simulate periodic mortality process

Usage

simulate_cycloSurv(
  n,
  period = 1,
  meanhazard = 0.5,
  peaks = c(0.25, 0.75),
  durations = c(0.2, 0.1),
  weights = c(0.5, 0.5),
  censoring = "random",
  censor.times = max.periods * period/2,
  max.periods = 10,
  n.times = 1000,
  plotme = TRUE
)

Arguments

n

number of simulated mortality/censoring events

period

length of one mortality cycle

meanhazard

average hazard value

peaks

k-vector of peaks

durations

k-vector of season length parameters, based on concentration parameter from wrapped Cauchy distribution

weights

k-vector of weights ((k-1)-vector is also accepted)

censoring

the type of censoring in the simulated data. Either "none" (all data is uncensored), "fixed" (all data is censored at a specified time), or "random" (data is randomly censored throughout).

censor.times

numeric or vector listing times for censoring (only applicable if censoring == "fixed").

max.periods

maximum number of cycles

n.times

number of x-values for plots (a higher value results in more precision for curves)

plotme

if TRUE, produces a set of plots for the simulation to display its accuracy

Value

a cycloSurv object (a type of Surv object; see Surv)

Examples

# NOT RUN {
par.init <- par(no.readonly = TRUE)
par(oma = c(2,0,2,0))
T.morts1 <- simulate_cycloSurv(1000, period = 1, 
                             meanhazard = 0.3, 
                             peaks = c(0.25, 0.75), 
                             durations = c(0.2, 0.1), 
                             weights = c(0.3, 0.7), 
                             plotme = TRUE)

with(attributes(T.morts1),
     title(paste0("mean hazard: ", meanhazard, "; peaks: ",
                  paste(peaks, collapse = ",")), outer = TRUE))

par(oma = c(2,0,2,0))
T.morts2 <- simulate_cycloSurv(300, period = 365, 
                             meanhazard = 0.5/365, 
                             peaks = c(100, 250), 
                             durations = c(20, 40), 
                             weights = c(0.4, 0.6), 
                             plotme = TRUE,
                             max.periods = 5)

with(attributes(T.morts2),
     title(paste0("mean hazard: ", round(meanhazard, 3), "; peaks: ",
                  paste(peaks, collapse = ",")), outer = TRUE))



par(mfrow = c(1,1))
require(magrittr)
h <- with(as.matrix(T.morts1) %>% data.frame %>% subset(status == 1),
    hist(stop - floor(stop), breaks = 20, col = "grey", bor = "darkgrey"))

with(attributes(T.morts1), curve(mwc(x, mus = peaks, 
                                     rhos = findRho(durations), gammas = weights, 
                                     tau = period)* mean(h$counts), add = TRUE))
par(par.init)
# }