Description Usage Arguments Value
View source: R/algo_farrington.R
Depending on the current transformation h(y)= \{y, √{y}, y^{2/3}\},
V(h(y_0)h(μ_0))=V(h(y_0))+V(h(μ_0))
is used to compute a prediction interval. The prediction variance consists of a component due to the variance of having a single observation and a prediction variance.
1  algo.farrington.threshold(pred,phi,alpha=0.01,skewness.transform="none",y)

pred 
A GLM prediction object 
phi 
Current overdispersion parameter (superflous?) 
alpha 
Quantile level in Gaussian based CI, i.e. an (1α)\cdot 100\% confidence interval is computed. 
skewness.transform 
Skewness correction, i.e. one of

y 
Observed number 
Vector of length four with lower and upper bounds of an
(1α)\cdot 100\% confidence interval (first two
arguments) and corresponding quantile of observation y
together with the median of the predictive distribution.
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