| int __stdcall NDK_WMA | ( | double * | pData, |
| size_t | nSize, | ||
| BOOL | bAscending, | ||
| double * | weights, | ||
| size_t | nwSize, | ||
| int | nHorizon, | ||
| double * | retVal | ||
| ) |
Returns the weighted moving (rolling/running) average using the previous m data points.
- Returns
- status code of the operation
- Return values
-
NDK_SUCCESS Operation successful NDK_FAILED Operation unsuccessful. See Macros for full list.
- Parameters
-
[in] pData is the univariate time series data (a one dimensional array). [in] nSize is the number of elements in pData. [in] bAscending is the time order in the data series (i.e. the first data point's corresponding date (earliest date=1 (default), latest date=0)). [in] weights is the size of the equal-weighted window or an array of multiplying factors (i.e. weights) of the moving/rolling window. [in] nwSize is the number of elements in the weights array. [in] nHorizon is the forecast time/horizon beyond the end of pData. If missing, a default value of 0 (Latest or end of pData) is assumed. [out] retVal is the calculated value of the weighted moving average.
- Remarks
-
- The time series is homogeneous or equally spaced.
- The time series may include missing values (NaN) at either end.
- The window size (m) must be less than the time series size, or else an error value (#VALUE!) is returned.
- The weights array should have a size greater than zero and consist of non-negative values.
- The size argument must match the actual size of the passed weight array, or else an error value (#VALUE) is returned.
- The weighted moving average in Excel (WMA) is defined as: \[ \mathit{wma}_t^k=\frac{\sum_{i=0}^{k-1} x_{t-k+i}\times w_i}{\sum_{i=0}^{k-1} w_i}\] Where:
- \(w_i\) is the weight of the i-th data point in the moving/rolling window.
- \(k\) is the size of the moving/rolling window.
- \(x_t\) is the value of the time series at time t.
- IMPORTANT: The first value in the weights array corresponds to the earliest point in the MA window.
- IMPORTANT: To exclude current observation from the moving average in Excel, set the last value (weight) in the given array to zero.
- The size of the weighted moving averqage time series is equal to the input time series.
- Requirements
-
Header SFSDK.H Library SFSDK.LIB DLL SFSDK.DLL
- Examples
-
| Namespace: | NumXLAPI |
| Class: | SFSDK |
| Scope: | Public |
| Lifetime: | Static |
| int NDK_WMA | ( | double[] | pData, |
| int | nSize, | ||
| BOOL | bAscending, | ||
| double[] | pWeights, | ||
| int | nwSize, | ||
| int | nHorizon, | ||
| ref double | retVal | ||
| ) |
Returns the weighted moving (rolling/running) average using the previous m data points.
- Returns
- status code of the operation
- Return values
-
NDK_SUCCESS Operation successful NDK_FAILED Operation unsuccessful. See Macros for full list.
- Parameters
-
[in] pData is the univariate time series data (a one dimensional array). [in] nSize is the number of elements in pData. [in] bAscending is the time order in the data series (i.e. the first data point's corresponding date (earliest date=1 (default), latest date=0)). [in] pWeights is the size of the equal-weighted window or an array of multiplying factors (i.e. weights) of the moving/rolling window. [in] nwSize is the number of elements in the weights array. [in] nHorizon is the forecast time/horizon beyond the end of pData. If missing, a default value of 0 (Latest or end of pData) is assumed. [out] retVal is the calculated value of the weighted moving average.
- Remarks
-
- The time series is homogeneous or equally spaced.
- The time series may include missing values (NaN) at either end.
- The window size (m) must be less than the time series size, or else an error value (#VALUE!) is returned.
- The weights array should have a size greater than zero and consist of non-negative values.
- The size argument must match the actual size of the passed weight array, or else an error value (#VALUE) is returned.
- The weighted moving average in Excel (WMA) is defined as: \[ \mathit{wma}_t^k=\frac{\sum_{i=0}^{k-1} x_{t-k+i}\times w_i}{\sum_{i=0}^{k-1} w_i}\] Where:
- \(w_i\) is the weight of the i-th data point in the moving/rolling window.
- \(k\) is the size of the moving/rolling window.
- \(x_t\) is the value of the time series at time t.
- IMPORTANT: The first value in the weights array corresponds to the earliest point in the MA window.
- IMPORTANT: To exclude current observation from the moving average in Excel, set the last value (weight) in the given array to zero.
- The size of the weighted moving averqage time series is equal to the input time series.
- 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
