Wrapper around the algo.cusum_with_reset Copied from the code of the surveillance package and adapted for algo.cusum_with_reset

Usage

cusum_with_reset(
  sts,
  control = list(range = range, k = 1.04, h = 2.26, m = NULL, trans = "standard", alpha =
    NULL),
  ...
)

Arguments

sts

surveillance::sts() format of aggregated timeseries of case counts

control

control object:

range

determines the desired time points which should be evaluated

k

is the reference value

h

the decision boundary

m

how to determine the expected number of cases – the following arguments are possible

numeric: a vector of values having the same length as range. If a single numeric value is specified then this value is replicated length(range) times.
NULL: A single value is estimated by taking the mean of all observations previous to the first range value.
"glm": A GLM of the form $$\log(m_t) = \alpha + \beta t + \sum_{s=1}^S (\gamma_s \sin(\omega_s t) + \delta_s \cos(\omega_s t)),$$ where $\omega_s = \frac{2\pi}{52}s$ are the Fourier frequencies is fitted. Then this model is used to predict the range values.

trans

one of the following transformations (warning: Anscombe and NegBin transformations are experimental)

rossi: standardized variables z3 as proposed by Rossi
standard: standardized variables z1 (based on asymptotic normality) - This is the default.
anscombe: anscombe residuals – experimental
anscombe2nd: anscombe residuals as in Pierce and Schafer (1986) based on 2nd order approximation of E(X) – experimental
pearsonNegBin: compute Pearson residuals for NegBin – experimental
anscombeNegBin: anscombe residuals for NegBin – experimental
none: no transformation

alpha

parameter of the negative binomial distribution, s.t. the variance is $m+\alpha *m^2$

reset

logical: Should the CUSUM statistic be reset to 0 immediately after an alarm? This is the traditional form of the chart as used in industrial process control, but not the default choice in outbreak detection when continuous periods of abnormal disease activity should be flagged.

...

any additional parameters which should be passed onto wrap.algo