Description Usage Arguments Details Value Author(s) References See Also Examples
best_distribution
computes the distribution assumption that
gives error intervals with the lower accuracy error for a given set of residuals.
1 2 | best_distribution(phi, errors, dists = c("n", "nm", "l", "lm", "w", "b",
"moge"), ...)
|
phi |
residual values used to compute the error interval. |
errors |
set of real errors corresponding to the predictions of a particular model. |
dists |
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
"b": Beta
"w": Weibull
"moge": Moge
Returns an object of class c("df_intervals", "data.frame")
with
information of the distribution assumption with lower accuracy error.
Jesus Prada, jesus.prada@estudiante.uam.es
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
df_intervals error_interval acc_intervals
1 | best_distribution(rnorm(10),rnorm(10),dists=c("n","b"))
|
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