TD_​ACF

The auto-covariance and auto-correlation function compute how a time series covaries or correlates with itself, when delayed by a particular lag. Example:For a lag equal to 1, we calculate the covariance or correlation between time series Yt and time series Yt-1 . for lag equal to 2, we calculate the covariance or correlation between time series Yt and time series Yt-2

Options

ALPHA

If a non-zero positive number is given, the confidence intervals for the given level are returned.For example, if alpha=.05 meaning the 95% level , then confidence intervals are returned where the standard deviation is computed according to Bartlett’s formula.Passing in a positive number results in a CONFINT result column being returned

DEMEAN

If 1 (default), then subtract the mean x from each element of x, as specified in the formulas for autocorrelation or autocovariance.If 0, then we do NOT do the subtraction on each element before computing the autocorrelation or autocovariance.

FUNC_TYPE

Specifies whether it is a auto-correlation or auto-covariance function.0 means execute the auto-correlation function. 1 means execute the auto-covariance function

MAXLAGS

Maximum number of lags at which to calculate the autocorrelation/autocovariance.Default is 10*log10(N) where N is the number of observations.Automatically limited to one less than the number of observations in the series.If the numLags value specified by the user exceeds this limit, the user input value is ignored and replaced with the system defined max value.

QSTAT

1 means provide Ljung-Box q statistic for each autocorrelation coefficient.0 (default) means do not provide. Requesting a QSTAT results in a QSTATVAL and PVALUE set of result columns being returned.

RoundResults

Determines whether rounding should be done or not. Passing in a value of '1' turns it ON.Passing in a value of '0' turns it OFF.If RoundResults(1), then results in the output row are rounded before inserting the row into the destination table (ART or response spool).

Output Schema

Output Schema, if Volatile is true then use user login as the schema.

Output Table

Output Table

VAL Location

VAL Location

Volatile

Specifies whether the table should be a VOLATILE table. If true, then the table is automatically deleted, otherwise it is users responsibility to remove or clean it up for space.

UNBIASED

If 0, then denominator for autocovariance is n-k (Jenkins & Watts formula)otherwise if 1, denominator for autocovariance is n (Box & Jenkins formula).

Nodes

• Integer Configuration5 ×
• String Configuration5 ×
• Python Script2 ×
• Boolean Configuration1 ×
• Component Input1 ×
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Extensions

• FeatureKNIME Base nodes
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• FeatureKNIME Quick Forms

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