algo.farrington.threshold {surveillance} | R Documentation |
Depending on the current transformation h(y)= {y, sqrt{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.
algo.farrington.threshold(pred,phi,alpha=0.01,skewness.transform="none",y)
pred |
A GLM prediction object |
phi |
Current overdispersion (superflous?) |
alpha |
Quantile level in Gaussian based CI, i.e. an (1-α)% confidence interval is computed. |
skewness.transform |
Skewness correction, i.e. one of
"none" , "1/2" , or "2/3" . |
y |
Observed number |
Vector of length 4 with lower and upper bounds of an (1-α)% confidence
interval (first two arguments) and corresponding quantile of observation y
together with the median of the predictive distribution.