summary.cv4abc: Calculates the cross-validation prediction error
Description
This function calculates the prediction error from an object of class
"cv4abc" for each parameter and tolerance level.
Usage
## S3 method for class 'cv4abc':
summary(object, print = TRUE, digits = max(3,
getOption("digits")-3), ...)
Arguments
object
an object of class "abc".
print
logical, if TRUE prints messages. Mainly for internal use.
digits
the digits to be rounded to. Can be a vector of the same length as the
number of parameters, when each parameter is rounded to its
corresponding digits.
...
other arguments passed to density.
Value
The returned value is an object of class "table", where the
columns correspond to the parameters and the rows to the different
tolerance levels.
Details
The prediction error is calculated as
$\frac{\sum((\theta^{*}-\theta)^2)}{nval\times Var(\theta)}$, where
$\theta$ is the true parameter value, $\theta^{*}$ is the
predicted parameter value, and $nval$ is the number of points where true and predicted values are compared.