Autocorrelation at Lag 1

Measures the autocorrelation of the forecast residuals at lag 1. Values close to zero indicate that residuals are uncorrelated, while values far from zero suggest the model is not capturing all available information.

Details

Computed as the sample autocorrelation of the residuals at lag 1 using stats::acf().

Dictionary

This mlr3::Measure can be instantiated via the dictionary mlr3::mlr_measures or with the associated sugar function mlr3::msr():

mlr_measures$get("fcst.acf1")
msr("fcst.acf1")

Meta Information

• Task type: “regr”

• Range: \([-1, 1]\)

• Minimize: NA

• Average: macro

• Required Prediction: “response”

• Required Packages: mlr3, mlr3forecast

Parameters

Empty ParamSet

See also

• Chapter in the mlr3book: https://mlr3book.mlr-org.com/chapters/chapter2/data_and_basic_modeling.html#sec-eval

• Package mlr3measures for the scoring functions.

• Dictionary of Measures: mlr3::mlr_measures

• as.data.table(mlr_measures) for a table of available Measures in the running session (depending on the loaded packages).

• Extension packages for additional task types:

  • mlr3proba for probabilistic supervised regression and survival analysis.

  • mlr3cluster for unsupervised clustering.

Other Measure: mlr_measures_fcst.coverage, mlr_measures_fcst.mase, mlr_measures_fcst.mda, mlr_measures_fcst.mdpv, mlr_measures_fcst.mdv, mlr_measures_fcst.mpe, mlr_measures_fcst.rmsse, mlr_measures_fcst.winkler

Super classes

mlr3::Measure -> mlr3::MeasureRegr -> MeasureACF1

Methods

Public methods

• MeasureACF1$new()

• MeasureACF1$clone()

Inherited methods

• mlr3::Measure$aggregate()
• mlr3::Measure$format()
• mlr3::Measure$help()
• mlr3::Measure$obs_loss()
• mlr3::Measure$print()
• mlr3::Measure$score()

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Method new()

Creates a new instance of this R6 class.

Usage

MeasureACF1$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

MeasureACF1$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.