estimateGLRNbHook {surveillance} | R Documentation |
Allows the user to specify his own estimation routine for the in-control mean of algo.glrpois
Needs to work for GLRNbHook
estimateGLRNbHook()
This hook function allows the user to customize the behaviour of the algorithm.
A list
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resulting model of a call of glm.nb |
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vector of length as range containing the predicted values |
M. Hoehle
## Not run: estimateGLRNbHook <- 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.nb(form,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)