Multivariate Surveillance through independent univariate algorithms
This function takes an sts
object and applies an univariate
surveillance algorithm to the time series of each observational unit.
wrap.algo(sts, algo, control,control.hook=function(k, control) return(control),verbose=TRUE,...) farrington(sts, control=list(range=NULL, b=5, w=3, reweight=TRUE, verbose=FALSE, alpha=0.05),...) bayes(sts, control = list(range = range, b = 0, w = 6, actY = TRUE,alpha=0.05),...) rki(sts, control = list(range = range, b = 2, w = 4, actY = FALSE),...) cusum(sts, control = list(range=range, k=1.04, h=2.26, m=NULL, trans="standard",alpha=NULL),...) glrpois(sts, control = list(range=range,c.ARL=5, S=1,beta=NULL, Mtilde=1, M=-1, change="intercept",theta=NULL),...) glrnb(sts, control = list(range=range,c.ARL=5, mu0=NULL, alpha=0, Mtilde=1, M=-1, change="intercept", theta=NULL,dir=c("inc","dec"), ret=c("cases","value")),...) outbreakP(sts, control=list(range = range, k=100, ret=c("cases","value"),maxUpperboundCases=1e5),...)
sts |
Object of class |
algo |
Character string giving the function name of the algorithm
to call, e.g. |
control |
Control object as list. Depends on each algorithm. |
control.hook |
This is a function for handling multivariate objects. This argument is a function function of integer k and the current control object and which returns the appropriate control object for region k. |
verbose |
Boolean, if |
... |
Additional arguments sent to the |
An sts
object with the alarm
, upperbound
,
etc. slots filled with the results of independent and univariate
surveillance algorithm.
M. Höhle
algo.rki
, algo.farrington
,
algo.cusum
, algo.glrpois
,
algo.glrnb
, algo.outbreakP
for the exact form of the control
object.
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.