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Boolean to indicate if order of AR components should be established automatically or if the given order should be used.
Since 2018.02 an attribute tag ("@ATTRIBUTE_ID@") can be given to use an attribute value of the output location instead. The used attribute must be a <boolean> attribute.
order_ar
Order of the AR model. If the orderSelection is true, then this value is the maximum order (may not exceed 50). 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.
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
Not 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).
parameters
This optional setting can be used to exactly specify the values for all the parameters (multipliers, powers, dividers, etc) used in the error correction model. An example is shown below. Please note that you will need to establish these parameters firs. One way to do this is to run a long historical run with auto-parameters on. The log file will show the parameters determined by the model. These parameters can be used to fix the parameters for the forecast.
Since 2018.02 attribute tags ("@ATTRIBUTE_ID@") can be used to determine the parameters 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).
subtractMean
Boolean to indicate if mean of residuals should be subtracted prior to establishing error model.
Since 2018.02 an attribute tag ("@ATTRIBUTE_ID@") can be given to use an attribute value of the output location instead. The used attribute must be a <boolean> attribute.
boxcoxTransformation
Boolean to indicate if the residuals should be transformed using Box-Cox transformation prior to establishing error model.
Since 2018.02 an attribute tag ("@ATTRIBUTE_ID@") can be given to use an attribute value of the output location instead. The used attribute must be a <boolean> attribute.
lambda
Lambda parameter to use in Box-Cox transformation (note: value of 0 means the transformation is a natural logarithm). Values ranging from 0 to 0.5 are often used.
Since 2018.02 attribute tags ("@ATTRIBUTE_ID@") can be used to determine the lambda 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).
ObservedTimeSeriesId
Input time series set to be defined as the observed data to compare simulated model output to.
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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.
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 part of the model. The order you specify determines the length of the period effected by the moving average function. The higher the order, the longer the effected period. The moving average model is not operational yet.
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).
ObservedTimeSeriesId
Input time series set to be defined as the observed data to compare simulated model output to.
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