Error model Sets element
All available error models present
Optional. Specify the log level for logging Error Model coefficients information. Default is 'debug'.
Error model
Interpolation options for filling the missing values of the Observed time series.
Maximum value to be used by error module. Higher values will be converted to NaN
Minimum value to be used by error module. Lower values will be converted to NaN
Maximum value to be generated by error module.
Minimum value to be generated by error module.
Should the error module ignore doubtful input values
If this is true, then all missing values after the last non-missing value in the simulated time series are ignored. If this is false, then gives an error message when there are missing values after the last non-missing value in the simulated time series. Default is false.
Since 2016.02. If this is true, then it is possible to configure locationSets in the input and output variables for this errorModel. This errorModel will then loop over these locations and run for each location separately. If this is false, then the observed input and output variables should contain only one location. Default is false. In any case, if the simulated input variables contain multiple time series for a given location, then these will be merged to create a single simulated input time series for that location. Note: looping over multiple ensemble members and/or qualifiers for the same location is not supported.
Optional. Specify the log level for the log message that is logged when all observed values are missing for a given input time series. Default is warn.
Option to determine if the orders are to be derived automatically (with the maximums as defined below) or as given by 'order_ar' and 'order_ma'. You can reference a boolean location attribute with @ATTRIBUTE_ID@. The output location's attributes will be used.
(maximum) order of the AR component, should be a value in the interval [0,50]. You can reference a numeric location attribute with @ATTRIBUTE_ID@. The output location's attributes will be used.
(maximum) order of the MA component, should be a value in the interval [0,50]. You can reference a numeric location attribute with @ATTRIBUTE_ID@. The output location's attributes will be used.
Option to determine if the mean is to be subtracted from the residuals. You can reference a boolean location attribute with @ATTRIBUTE_ID@. The output location's attributes will be used.
Option to apply a boxcox transformation to residuals. You can reference a boolean location attribute with @ATTRIBUTE_ID@. The output location's attributes will be used.
A required parameter for theboxcox transformation option. You can reference a numeric location attribute with @ATTRIBUTE_ID@. The output location's attributes will be used.
Limit data window used to establish AR parameters
Observed times series data
Simulated data generated by model. This series can contain data for the historic and forecast period.
Multiple series will be combined into single series. Series with higher index will be overlayed by series with lower index.
Updated time series data generated by the error model. This series can contain data for the historic and forecast period. Note: this is never used in the code, because there can be only one outputVariable.
(maximum) order of the AR component, should be a value in the interval [0,50]. You can reference a numeric location attribute with @ATTRIBUTE_ID@. The output location's attributes will be used.
(maximum) order of the ARMA component, should be a value in the interval [0,50]. You can reference a numeric location attribute with @ATTRIBUTE_ID@. The output location's attributes will be used.
Observed times series data
Simulated data generated by model. This series can contain data for the historic and forecast period.
Multiple series will be combined into single series. Series with higher index will be overlayed by series with lower index.
Updated time series data generated by the error model. This series can contain data for the historic and forecast period. Note: this is never used in the code, because there can be only one outputVariable.
Maximum allowed gap size that can be filled using interpolation.
Default value required for 'defaultValue' interpolation option.
Fixed parameters to use in the error model. You can reference a numeric location attribute with @ATTRIBUTE_ID@. The output location's attributes will be used.
Log error message.
Log warning message.
Log info message.
Log info message.