Converts time series data to a lagged format used as input to a neural
network.
Namespace:
Imsl.DataMining.NeuralAssembly: ImslCS (in ImslCS.dll) Version: 6.5.0.0
Syntax
C# |
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[SerializableAttribute] public class TimeSeriesFilter |
Visual Basic (Declaration) |
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<SerializableAttribute> _ Public Class TimeSeriesFilter |
Visual C++ |
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[SerializableAttribute] public ref class TimeSeriesFilter |
Remarks
Class TimeSeriesFilter can be used to operate on a data matrix and lags every column to form a new data matrix. Using the method ComputeLags, each column of the input matrix, x, is transformed into (nLags+1) columns by creating a column for .
The output data array, z, can be symbolically represented as:
where x[i] is a lagged column of the incoming data matrix, x.Consider, an example in which x has five rows and two columns with all variables continuous input attributes. Using nObs and nVar to represent the number of rows and columns in x, let
If nLags=1, then the number of columns in z[,] is nVar*(nLags+1) = 2*2 = 4, and the number of rows is (nObs-nLags) = 5-1 = 4: If nLags=2, then the number of rows in z will be (nObs-nLags) = (5-2) = 3 and the number of columns will be nVar*(nLags+1) = 2*3 = 6: