algo.cusum {surveillance} | R Documentation |
Approximate one-side CUSUM method for a Poisson variate based on the cumulative sum of the deviation between a reference value k and the (standardized) observed values. An alarm is raised if the cumulative sum equals or exceeds a prespecified decision boundary h.
algo.cusum(disProgObj, control = list(range = range, k = 1.04, h = 2.26, m = NULL, trans = "standard", alpha = NULL))
disProgObj |
object of class disProg (including the observed and the state chain) |
control |
control object:
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This implementation is still experimental
survRes |
algo.cusum gives a list of class survRes which includes the
vector of alarm values for every timepoint in range and the vector
of cumulative sums for every timepoint in range for the system
specified by k and h , the range and the input object of
class disProg.
The upperbound entry shows for each time instance the number of diseased individuals
it would have taken the cusum to signal. Once the CUSUM signals no resetting is applied, i.e.
signals occurs until the CUSUM statistic again returns below the threshold.
The control$m.glm entry contains the fitted glm object, if
the original argument was "glm ".
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M. Paul and M. Höhle
G. Rossi, L. Lampugnani and M. Marchi (1999), An approximate CUSUM procedure for surveillance of health events, Statistics in Medicine, 18, 2111–2122
D. A. Pierce and D. W. Schafer (1986), Residuals in Generalized Linear Models, Journal of the American Statistical Association, 81, 977–986
# Xi ~ Po(5), i=1,...,500 disProgObj <- create.disProg(week=1:500, observed= rpois(500,lambda=5), state=rep(0,500)) # there should be no alarms as mean doesn't change res <- algo.cusum(disProgObj, control = list(range = 100:500,trans="anscombe")) plot(res) # simulated data disProgObj <- sim.pointSource(p = 1, r = 1, length = 250, A = 0, alpha = log(5), beta = 0, phi = 10, frequency = 10, state = NULL, K = 0) plot(disProgObj) # Test week 200 to 250 for outbreaks surv <- algo.cusum(disProgObj, control = list(range = 200:250)) plot(surv)