algo.farrington.threshold: Compute prediction interval for a new observation
Description
Depending on the current transformation $h(y)= {y, \sqrt{y}, y^{2/3}}$,
$$V(h(y_0)-h(\mu_0))=V(h(y_0))+V(h(\mu_0))$$
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.
Quantile level in Gaussian based CI, i.e. an $(1-\alpha)\cdot 100%$
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 four with lower and upper bounds of an
$(1-\alpha)\cdot 100%$ confidence interval (first two
arguments) and corresponding quantile of observation y
together with the median of the predictive distribution.