The Fit companion object provides factory methods for assessing quality of fit for standard types of modeling techniques.
Attributes
Members list
Value members
Concrete methods
Return a contrary/starting value, -∞ for maximization, ∞ for minimization
Return a contrary/starting value, -∞ for maximization, ∞ for minimization
Value parameters
- qk
-
the QoF metric index/ordinal value
Attributes
Return the help string that describes the Quality of Fit (QoF) measures provided by the Fit trait. The QoF measures are divided into two groups: general and statistical (that often require degrees of freedom and/or log-likelihoods).
Return the help string that describes the Quality of Fit (QoF) measures provided by the Fit trait. The QoF measures are divided into two groups: general and statistical (that often require degrees of freedom and/or log-likelihoods).
Attributes
- See also
-
en.wikipedia.org/wiki/Coefficient_of_determination
Return the Interval Score (IS) metric, i.e., the ...
Return the Interval Score (IS) metric, i.e., the ...
Value parameters
- low
-
the lower bound
- up
-
the upper bound & @param alpha the prediction level
- y
-
the given time-series (must be aligned with the interval forecast)
Attributes
- See also
-
arxiv.org/pdf/2005.12881.pdf
Return the Mean Absolute Error (MAE) for the forecasting model under test.
Return the Mean Absolute Error (MAE) for the forecasting model under test.
Value parameters
- h
-
the forecasting horizon or stride (defaults to 1)
- y
-
the given time-series (must be aligned with the forecast)
- yp
-
the forecasted time-series
Attributes
Return the Mean Absolute Error (MAE) for the Naive Model (simple random walk) with horizon/stride h. For comparison with the above method.
Return the Mean Absolute Error (MAE) for the Naive Model (simple random walk) with horizon/stride h. For comparison with the above method.
Value parameters
- h
-
the forecasting horizon or stride (defaults to 1)
- y
-
the given time-series
Attributes
Return the Mean Absolute Scaled Error (MASE) for the given time-series. It is the ratio of MAE of the forecasting model under test and the MAE of the Naive Model (simple random walk).
Return the Mean Absolute Scaled Error (MASE) for the given time-series. It is the ratio of MAE of the forecasting model under test and the MAE of the Naive Model (simple random walk).
Value parameters
- h
-
the forecasting horizon or stride (defaults to 1)
- y
-
the given time-series (must be aligned with the forecast)
- yp
-
the forecasted time-series
Attributes
Return the Prediction Interval Coverage Probability (PICP) metric, i.e., the fraction is actual values inside the prediction interval.
Return the Prediction Interval Coverage Probability (PICP) metric, i.e., the fraction is actual values inside the prediction interval.
Value parameters
- low
-
the lower bound
- up
-
the upper bound
- y
-
the given time-series (must be aligned with the interval forecast)
Attributes
Return the Prediction Interval Normalised Average Deviation (PINAD) metric, i.e., the normalized (by range) average deviation outside the prediction interval.
Return the Prediction Interval Normalised Average Deviation (PINAD) metric, i.e., the normalized (by range) average deviation outside the prediction interval.
Value parameters
- low
-
the lower bound
- up
-
the upper bound
- y
-
the given time-series (must be aligned with the interval forecast)
Attributes
Create a table to store statistics for QoF measures, where each row corresponds to the statistics on a particular QoF measure, e.g., rSq.
Create a table to store statistics for QoF measures, where each row corresponds to the statistics on a particular QoF measure, e.g., rSq.
Attributes
Collect QoF results for a model and return them in a vector.
Collect QoF results for a model and return them in a vector.
Value parameters
- cv_fit
-
the fit array of statistics for cross-validation (upon test sets)
- fit
-
the fit vector with regard to the training set
Attributes
Tally the current QoF measures into the statistical accumulators.
Tally the current QoF measures into the statistical accumulators.
Value parameters
- qof
-
the current QoF measure vector
- stats
-
the statistics table being updated
Attributes
Return the Weighted Interval Score (WIS) metric, i.e., the ...
Return the Weighted Interval Score (WIS) metric, i.e., the ...
Value parameters
- alphas
-
the array of prediction levels
- low
-
the lower bounds for various alpha levels
- up
-
the upper bounds for various alpha levels
- y
-
the given time-series (must be aligned with the interval forecast)
- yp
-
the point prediction mean/median
Attributes
- See also
-
arxiv.org/pdf/2005.12881.pdf