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<singleValueModifier id="wechng" name="wechng">
		<timeSeries>
			<parameterId>WECHNG</parameterId>
		</timeSeries>
		<softLimits>
			<maximumValue>25</maximumValue>
			<minimumValue>0</minimumValue>
		</softLimits>
		<hardLimits>
			<maximumValue>100</maximumValue>
			<minimumValue>0</minimumValue>
		</hardLimits>
		<defaultValue>5<<defaultTime>time zero</defaultTime>
		<defaultValue>1</defaultValue>
</singleValueModifier>

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It is possible to assign a default value to a single value modifier.

The following options are available:

default value

derive a default value from a time series

derive default value from a statistical function

In the config example above a default value is configured as the initial value for the modifier.

Below a summary of the options which can be used to define the initial value of the modifier.

default value

This option defines a hard-code value as the initial value for the modifier

derive a default value from a time series

This option defines a set of time series. The initial value will be derived from the time series which has the same location as the location of the modifier.

From this time series the the value at the time of the modifier will be chosen.

derive default value from a statistical functionWhen a default value is configured the modifier will always default to that value.
In case the second option is chosen than it is possible to define a timeseries-filter from which the default value should be derived.
The modifier will look for a value at the time for which the modifier is defined.

The last option allows the forecaster to configure a statistical function from which the value should be derived.
Currently only the principal component analysis-functions support this option.

When the principal component analysis is run in the plot display by selecting the principal component analysis-function the output value of this function will be default value for the modifier.

Constant value modifiers

Constant value modifiers are very similar to single value modifiers. But instead of modifying a single value at a
particular point in time, they modify a time series over a period of time with a fixed value.

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