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What | nameofinstance.xml |
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Description | Configuration o the ARMA module |
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<description>Applies error correction module</description>
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GreatCorby_ErrorModel_Forecast 1.00 default.xml
GreatCorby_ErrorModel_Forecast | File name for the GreatCorby_ErrorModel_Forecast configuration. |
1.00 | Version number |
default | Flag to indicate the version is the default configuration (otherwise omitted). |
Figure 86 Elements of the error module configuration.
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Definition of input variable to be used in the error correction model. At least two entries are required in the error model, one for observed time series and one for simulated time series For each entry an input variable will need to be identified. The variableId is used to refer to the time series. See Transformation Module for definition of inputVariable configuration. It is not possible to use LocationSets in the TimeSerieSet definition, so it is required to define an ErrorModelSet per location.
TimeSerieSet
ConvertDatum is not supported in the ARMA module. The input timeseries should be in the same datum.
autoOrderMethod
Root element for defining an error model using the AR structure.
Figure 87 Elements of the autoOrderMethod configuration.
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Since 2018.02 attribute tags ("@ATTRIBUTE_ID@") can be used to determine the order_ar using attribute values of the output location. The used attributes must be a <number> or <boolean> attribute (in the case of <boolean> the "true" value will be interpreted as 1 and the "false" value as 0).
order_ma
Order of the MA model. If the orderSelection is true, then this value is used as the maximum order. In this case, for a given ar order, the corresponding ma order will always be calculated as follows: maOrder = arOrder - (maxArOrder - maxMaOrder). During the order optimization process, each ar order for which this results in a valid ma order will be tried.
For example, if the configured <order_ar> is 5 and the configured <order_ma> is 2, then the order optimization process will attempt an arOrder of 0 (special case), 3, 4, and 5. The ar orders of 1 and 2 will be omitted since they would result in a negative ma orderNot used in this method.
Since 2018.02 attribute tags ("@ATTRIBUTE_ID@") can be used to determine the order_ma using attribute values of the output location. The used attributes must be a <number> or <boolean> attribute (in the case of <boolean> the "true" value will be interpreted as 1 and the "false" value as 0).
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Updated timeseries data generated by the error model. This serie can contain data for the historic and the forecast period.
fixedOrderMethod
Root element for defining an error model using the ARMA structure.
Figure 88 Elements of the fixedOrderMethod configuration.
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- none
- ARMA+ systematic
- systematic
- ARMA
- ARMA+ log transformation
- ARMA+ systematic+ log transformation
order_ar
Order of the AR part of the model. In literature mostly an value of the AR order up to 3 is chosen, higher values are possible, but will have a smaller contribution to the overall result of the error correction.
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Default value required for 'defaultvalue' interpolation option.
maxObserved
Maximum value to be used by the error module. Higher values will be converted to NaN and not used as input for error correction. This parameter is optional.
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Option 'logLevelCoefficientsInfo' is set in ErrorModelSetsComplexType directly under element 'errorModelSet'. The value defaults to 'debug', such that the computed coefficients are only logged when the module is run in debug mode. Set the value to 'info' to show the coefficients in the standard logging.