Description Usage Arguments References Examples
Function for simulating a time series and creating a sts-object As the counts are generated using a negative binomial distribution one also gets the (1-alpha) quantile for each timepoint (can be interpreted as an in-control upperbound for in-control values). The baseline and outbreaks are created as in Noufaily 2012.
1 2 | sts_creation(theta, beta, gamma1, gamma2, m, overdispersion, dates,
sizesOutbreak, datesOutbreak, delayMax, alpha, densityDelay)
|
theta |
baseline frequency of reports |
beta |
time trend |
gamma1 |
seasonality |
gamma2 |
seasonality |
m |
seasonality |
overdispersion |
overdispersion (size in rnbinom for the parameterization with mean and size) |
dates |
dates of the time series |
sizesOutbreak |
sizes of all the outbreaks (vector) |
datesOutbreak |
dates of all the outbreaks (vector) # alpha |
delayMax |
maximal delay in time units |
alpha |
alpha for getting the (1-alpha) quantile of the negative binomial distribution at each timepoint |
densityDelay |
density distribution for the delay |
An improved algorithm for outbreak detection in multiple surveillance systems, Noufaily, A., Enki, D.G., Farrington, C.P., Garthwaite, P., Andrews, N.J., Charlett, A. (2012), Statistics in Medicine, published online.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | set.seed(12345)
# Time series parameters
scenario4 <- c(1.6,0,0.4,0.5,2)
theta <- 1.6
beta <- 0
gamma1 <-0.4
gamma2 <- 0.5
overdispersion <- 1
m <- 1
# Dates
firstDate <- "2006-01-01"
lengthT=350
dates <- as.Date(firstDate,origin='1970-01-01') + 7 * 0:(lengthT - 1)
# Maximal delay in weeks
D=10
# Dates and sizes of the outbreaks
datesOutbreak <- c(as.Date("2008-03-30"),as.Date("2011-09-25",origin="1970-01-01"))
sizesOutbreak <- c(2,5)
# Delay distribution
data("salmAllOnset")
in2011 <- which(formatDate(epoch(salmAllOnset), "%G") == 2011)
rT2011 <- salmAllOnset@control$reportingTriangle$n[in2011,]
densityDelay <- apply(rT2011,2,sum, na.rm=TRUE)/sum(rT2011, na.rm=TRUE)
# alpha for the upperbound
alpha <- 0.05
# Create the sts with the full time series
stsSim <- sts_creation(theta=theta,beta=beta,
gamma1=gamma1,gamma2=gamma2,
m=m,overdispersion=overdispersion
,dates=dates,sizesOutbreak=sizesOutbreak,
datesOutbreak=datesOutbreak,
delayMax=D,
densityDelay=densityDelay,
alpha=alpha)
plot(stsSim)
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