evaluating: Prediction/modeling quality evaluation

In TSPred: Functions for Benchmarking Time Series Prediction

Prediction/modeling quality evaluation

Description

Constructor for the evaluating class representing a time series prediction or modeling fitness quality evaluation based on a particular metric. The evaluating class has two specialized subclasses fitness and error reagarding fitness criteria and prediction/modeling error metrics, respectively.

Usage

evaluating(eval_func, eval_par = NULL, ..., subclass = NULL)

fitness(eval_func, eval_par = NULL, ..., subclass = NULL)

error(eval_func, eval_par = NULL, ..., subclass = NULL)

Arguments

eval_func	A function for computing a particular metric.
eval_par	List of named parameters required by eval_func.
...	Other parameters to be encapsulated in the class object.
subclass	Name of new specialized subclass object created in case it is provided.

Value

An object of class evaluating. A list usually containing at least the following elements:

func	A function for computing a particular metric.
par	Particular parameters required by func.

Author(s)

Rebecca Pontes Salles

See Also

Other constructors: ARIMA(), LT(), MSE_eval(), modeling(), processing(), tspred()

Examples

e <- error(eval_func=TSPred::NMSE, eval_par=list(train.actual=NULL),
           method="Normalised Mean Squared Error", subclass="NMSE")
summary(e)

f <- fitness(eval_func=stats::AIC, method="Akaike's Information Criterion", subclass="AIC")
summary(f)

TSPred documentation built on June 11, 2025, 1:07 a.m.