Description Usage Arguments Value Author(s) References Examples

The Diebold-Mariano test compares the forecast accuracy of two forecast methods. The null hypothesis is that they have the same forecast accuracy.

1 2 |

`e1` |
Forecast errors from method 1. |

`e2` |
Forecast errors from method 2. |

`alternative` |
a character string specifying the alternative hypothesis, must be one of |

`h` |
The forecast horizon used in calculating |

`power` |
The power used in the loss function. Usually 1 or 2. |

A list with class `"htest"`

containing the following components:

`statistic` |
the value of the DM-statistic. |

`parameter` |
the forecast horizon and loss function power used in the test. |

`alternative` |
a character string describing the alternative hypothesis. |

`p.value` |
the p-value for the test. |

`method` |
a character string with the value "Diebold-Mariano Test". |

`data.name` |
a character vector giving the names of the two error series. |

George Athanasopoulos and Rob Hyndman

Diebold, F.X. and Mariano, R.S. (1995) Comparing predictive accuracy. *Journal of Business
and Economic Statistics*, **13**, 253-263.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
# Test on in-sample one-step forecasts
f1 <- ets(WWWusage)
f2 <- auto.arima(WWWusage)
accuracy(f1)
accuracy(f2)
dm.test(residuals(f1),residuals(f2),h=1)
# Test on out-of-sample one-step forecasts
f1 <- ets(WWWusage[1:80])
f2 <- auto.arima(WWWusage[1:80])
f1.out <- ets(WWWusage[81:100],model=f1)
f2.out <- Arima(WWWusage[81:100],model=f2)
accuracy(f1.out)
accuracy(f2.out)
dm.test(residuals(f1.out),residuals(f2.out),h=1)
``` |

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