Description Usage Details Value Author(s) See Also Examples
Allows the user to specify his own estimation routine for the in-control mean of algo.glrpois
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This hook function allows the user to customize the behaviour of the algorithm.
A vector of length as range
containing the predicted values.
M. Hoehle
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 | ## Not run:
estimateGLRPoisHook <- function() {
#Fetch control object from parent
control <- parent.frame()$control
#The period
p <- parent.frame()$disProgObj$freq
#Current range to perform surveillance on
range <- parent.frame()$range
#Define training & test data set (the rest)
train <- 1:(range[1]-1)
test <- range
#Perform an estimation based on all observations before timePoint
#Event better - don't do this at all in the algorithm - force
#user to do it himself - coz its a model selection problem
data <- data.frame(y=parent.frame()$disProgObj$observed[t],t=train)
#Build the model equation
formula <- "y ~ 1 "
if (control$mu0Model$trend) { formula <- paste(formula," + t",sep="") }
for (s in 1:control$mu0Model$S) {
formula <- paste(formula,"+cos(2*",s,"*pi/p*t)+ sin(2*",s,"*pi/p*t)",sep="")
}
#Fit the GLM
m <- eval(substitute(glm(form,family=poisson(),data=data),list(form=as.formula(formula))))
#Predict mu_{0,t}
return(as.numeric(predict(m,newdata=data.frame(t=range),type="response")))
}
## End(Not run)
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