acc_intervals: Accuracy of Error intervals

In errint: Builds Error Intervals

Description

int_intervals computes the real accuracy of a given error intervals for a particular set of errors and a particular error function.

Usage

acc_intervals(interv, errors, f = function(x, y) {     abs(x - y) },
  tol = 10^-8)

Arguments

interv	error interval.
errors	set of errors.
f	error function to be used to compute error between real x (interv) and predicted y (errors) values. See also 'Details'.
tol	used to normalize residual values to (0,1) when beta is the assumed distribution. See also 'Details'.

Details

f must be a function that takes two arguments, x and y, and return a numeric value.

The formula used to normalize residual values to (0,1) when a Beta distribution is assumed is |φ|*(max(|φ|)+tol)^(-1).

Value

Returns an object of class c("measure","list") with information of the interval accuracy.

Author(s)

Jesus Prada, [e-mail]

References

Link to the scientific paper

Prada, Jesus, and Jose Ramon Dorronsoro. "SVRs and Uncertainty Estimates in Wind Energy Prediction." Advances in Computational Intelligence. Springer International Publishing, 2015. 564-577,

with theoretical background for this package is provided below.

http://link.springer.com/chapter/10.1007/978-3-319-19222-2_47

See Also

measure error_interval

Examples

interv<-int_gau(rnorm(10),0.1)
acc_intervals(interv,rnorm(10))
acc_intervals(interv,rnorm(10),function(x,y){x-y})

errint documentation built on May 1, 2019, 10:06 p.m.