best_distribution computes the distribution assumption that
gives error intervals with the lower accuracy error for a given set of residuals.
residual values used to compute the error interval.
set of real errors corresponding to the predictions of a particular model.
character vector with the distribution assumptions to test. See also 'Details'.
additional arguments to be passed to functions
Allowed distribution assumptions are:
"n": Zero-mu Gaussian
"nm": General Gaussian
"l": Zero-mu Laplace
"lm": General Laplace
Returns an object of class
c("df_intervals", "data.frame") with
information of the distribution assumption with lower accuracy error.
Jesus Prada, firstname.lastname@example.org
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.
df_intervals error_interval acc_intervals
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