# NDK_INTERP_NAN

 int __stdcall NDK_INTERP_NAN ( double * X, size_t N, WORD nMethod, double plug )

Returns an array of a time series after substituting all missing values with the mean/median.

Returns
status code of the operation
Return values
 NDK_SUCCESS Operation successful NDK_FAILED Operation unsuccessful. See Macros for full list.
NDK_INTERPOLATE()
Parameters
[in,out] is the univariate time series data (a one dimensional array).
[in] is the number of observations in X.
[in] nMethod  is an identifier for the method used to generate values for any missing data:
Method Value
Mean (default) 1
Median 2
Constant 3
Forward 4
Backward 5
Linear 6
Cubic spline 7
Weighted moving average 8
Exponential smoothing 9
Brownian bridge 10
[in] plug  is the data argument related to the selected treatment method (if applicable). For instance, if the method is constant, then the value would be the actual value.
Remarks
1. The time series is homogeneous or equally spaced.
2. The function operates only on intermediate missing values. Missing values on both sides are left unchanged.
3. The function maintains the original time-order of the data set.
Requirements
Examples



 Namespace: NumXLAPI Class: SFSDK Scope: Public Lifetime: Static
 int NDK_INTERP_NAN ( double[] pData, UIntPtr nSize, short nMethod, double plug )

Returns an array of a time series after substituting all missing values with the mean/median.

Returns
status code of the operation
Return values
 NDK_SUCCESS Operation successful NDK_FAILED Operation unsuccessful. See Macros for full list.
NDK_INTERPOLATE()
Parameters
[in,out] pData  is the univariate time series data (a one dimensional array).
[in] nSize  is the number of observations in pData.
[in] nMethod  is an identifier for the method used to generate values for any missing data:
Method Value
Mean (default) 1
Median 2
Constant 3
Forward 4
Backward 5
Linear 6
Cubic spline 7
Weighted moving average 8
Exponential smoothing 9
Brownian bridge 10
[in] plug  is the data argument related to the selected treatment method (if applicable). For instance, if the method is constant, then the value would be the actual value.
Remarks
1. The time series is homogeneous or equally spaced.
2. The function operates only on intermediate missing values. Missing values on both sides are left unchanged.
3. The function maintains the original time-order of the data set.
Exceptions
Exception Type Condition
None N/A
Requirements
Namespace NumXLAPI SFSDK Public Static 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