| int __stdcall NDK_LRVAR | ( | double * | X, |
| size_t | N, | ||
| size_t | W, | ||
| double * | retVal | ||
| ) |
Returns the long-run variance using a Bartlett kernel with window size k.
- 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 input data sample (a one/two dimensional array). [in] N is the number of observations in X. [in] w is the input Bartlett kernel window size. If omitted, the default value is the cubic root of the sample data size. [out] retVal is the calculated value of this function.
- Remarks
- 1. The input time series data may include missing values (NaN), but they will not be included in the calculations.
- 2. The long-run variance is computed as follows:
- \[\sigma^2=\frac{1}{T}\sum_{t=k}^{T-k}\sum_{i=-k}^k w_i(x_t-\bar{x})(x_{t-i}-\bar{x})\]
- Where:
- \(x_{t} \in X\) is a value from the input time series data.
- \(\bar{x}\) is the mean of the input time series data.
- \(w_i\) is the Bartlett kernel weight, and it is defined as follows:
- \(w_i= 1- \frac{\left | i \right |}{k+1}\)
- \(k\) is the input window size for the Bartlett kernel.
- Requirements
-
Header SFSDK.H Library SFSDK.LIB DLL SFSDK.DLL
- Examples
-
| Namespace: | NumXLAPI |
| Class: | SFSDK |
| Scope: | Public |
| Lifetime: | Static |
| int NDK_LRVAR | ( | double[] | pData, |
| UIntPtr | nSize, | ||
| short | argMenthod, | ||
| ref double | retVal | ||
| ) |
Returns the long-run variance using a Bartlett kernel with window size k.
- Return Value
-
a value from NDK_RETCODE enumeration for the status of the call.
NDK_SUCCESS operation successful Error Error Code
- Parameters
-
[in] pData is the input data sample (a one/two dimensional array). [in] nSize is the number of observations in pData. [in] argMenthod is the input Bartlett kernel window size. If omitted, the default value is the cubic root of the sample data size. [out] retVal is the calculated value of this function.
- Remarks
- 1. The input time series data may include missing values (NaN), but they will not be included in the calculations.
- 2. The long-run variance is computed as follows:
- \[\sigma^2=\frac{1}{T}\sum_{t=k}^{T-k}\sum_{i=-k}^k w_i(x_t-\bar{x})(x_{t-i}-\bar{x})\]
- Where:
- \(x_{t} \in X\) is a value from the input time series data.
- \(\bar{x}\) is the mean of the input time series data.
- \(w_i\) is the Bartlett kernel weight, and it is defined as follows:
- \(w_i= 1- \frac{\left | i \right |}{k+1}\)
- \(k\) is the input window size for the Bartlett kernel.
- 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
