NDK_CONVOLUTION

int __stdcall NDK_CONVOLUTION ( double *  X,
size_t  N1,
double *  Y,
size_t  N2,
double *  Z,
size_t * 
)

Returns an array of cells for the convolution operator of two time series.

Returns
status code of the operation
Return values
NDK_SUCCESS  Operation successful
NDK_FAILED  Operation unsuccessful. See Macros for full list.
Parameters
[in] X is the univariate time series data (a one dimensional array).
[in] N1   is the number of observations in X.
[in] Y is the second univariate time series data (a one dimensional array)
[in] N2  is the number of observations in Y.
[out] Z is the convolution time series output
[in,out] W is the maximum number of elements in Z.
Remarks
  1. The time series must be homogeneous or equally spaced.
  2. The two time series can have different sizes.
  3. Presample values of \(X_t\) and \(Y_t\) are assumed to be zero
  4. The convolution operator is described as follow: \[ Z_t=\sum_{j=\mathit{max}\left ( 1,t-M+1 \right )}^{\mathit{min}\left ( N,t+M-1 \right )}X_jY_{M-t+j}\] Where:
    • \(Z_t\) is the convolution time series
    • \(X_t\) is the first time series, with \(N\) observations
    • \(Y_t\) is the second time series, with \(M\) observations.
    • \(t\in \left[ 1,N+M \right]\), i.e., \(1\leq t \leq N+M\).
Requirements
Header SFSDK.H
Library SFSDK.LIB
DLL SFSDK.DLL
Examples


   
Namespace:  NumXLAPI
Class:  SFSDK
Scope:  Public
Lifetime:  Static
int NDK_CONVOLUTION ( double[]  pData1,
UIntPtr  nSize1,
double[]  pData2,
UIntPtr  nSize2,
out double  pResult,
out UIntPtr  nWindowSize 
)

Returns an array of cells for the convolution operator of two time series.

Return Value

a value from NDK_RETCODE enumeration for the status of the call. 

NDK_SUCCESS  operation successful
Error  Error Code
Parameters
[in] pData1 is the univariate time series data (a one dimensional array).
[in] nSize1   is the number of observations in pData1.
[in] pData2 is the second univariate time series data (a one dimensional array)
[in] nSize2  is the number of observations in pData2.
[out] pResult is the convolution time series output
[in,out] nWindowSize is the maximum number of elements in Z.
Remarks
  1. The time series must be homogeneous or equally spaced.
  2. The two time series can have different sizes.
  3. Presample values of \(X_t\) and \(Y_t\) are assumed to be zero
  4. The convolution operator is described as follow: \[ Z_t=\sum_{j=\mathit{max}\left ( 1,t-M+1 \right )}^{\mathit{min}\left ( N,t+M-1 \right )}X_jY_{M-t+j}\] Where:
    • \(Z_t\) is the convolution time series
    • \(X_t\) is the first time series, with \(N\) observations
    • \(Y_t\) is the second time series, with \(M\) observations.
    • \(t\in \left[ 1,N+M \right]\), i.e., \(1\leq t \leq N+M\).
Exceptions
Exception Type Condition
None N/A
Requirements
Namespace NumXLAPI
Class SFSDK
Scope Public
Lifetime Static
Package NumXLAPI.DLL
Examples
	
References
* Hamilton, J .D.; Time Series Analysis , Princeton University Press (1994), ISBN 0-691-04289-6
* Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0-471-690740
* D. S.G. Pollock; Handbook of Time Series Analysis, Signal Processing, and Dynamics; Academic Press; Har/Cdr edition(Nov 17, 1999), ISBN: 125609906
* Box, Jenkins and Reisel; Time Series Analysis: Forecasting and Control; John Wiley & SONS.; 4th edition(Jun 30, 2008), ISBN: 470272848