algo.farrington.threshold {surveillance}R Documentation

Threshold computations using a two sided confidence interval

Description

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.

Usage

algo.farrington.threshold(pred,phi,alpha=0.01,skewness.transform="none",y)

Arguments

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

Value

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.


[Package surveillance version 1.1-2 Index]