View source: R/wrap_univariate.R
wrap.algo | R Documentation |
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,...)
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 |
... |
currently ignored. |
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.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.