| int __stdcall NDK_MD | ( | double * | pData, |
| size_t | nSize, | ||
| WORD | reserved, | ||
| double * | retVal | ||
| ) |
Returns the mean difference of the input data series.
- 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 input data series (one/two dimensional array). [in] nSize is the number of observations in pData. [in] reserved This parameter is reserved and must be 1. [out] retVal is the computed value.
- Remarks
- 1. The time series may include missing values (NaN), but they will not be included in the calculations.
- 2. The sample mean difference (MD) is computed as follows:
- \[\Delta = \mathrm{MD} = \frac{\sum_{i=1}^n \sum_{j=1}^n \| x_i - x_j \|}{n \times \left ( n-1 \right )}\]
- Where:
- \(x_i\) is the value of the i-th non-missing observation.
- \(n\) is the number of non-missing observations in the sample.
- 4. The mean difference is the product of the sample mean and the relative mean difference (RMD) and so can also be expressed in terms of the NDK_GINI:
- \[\mathrm{MD}= 2 \times G \times \bar{x}\]
- Where:
- \(\bar{x}\) is the arithmetic sample mean.
- \(G\) is the NDK_GINI.
- 6. Because of its ties to the Gini coefficient, the mean difference is also called the "Gini mean difference." It is also known as the "absolute mean difference."
- 7. The sample mean difference is not dependent on a specific measure of central tendency like the standard deviation.
- 8. The mean difference of a sample is an unbiased and consistent estimator of the population mean difference.
- Requirements
-
Header SFSDK.H Library SFSDK.LIB DLL SFSDK.DLL
- Examples
-
| Namespace: | NumXLAPI |
| Class: | SFSDK |
| Scope: | Public |
| Lifetime: | Static |
| int NDK_MD | ( | double[] | pData, |
| UIntPtr | nSize, | ||
| short | argMenthod, | ||
| ref double | retVal | ||
| ) |
Returns the mean difference of the input data series.
- 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 series (one/two dimensional array). [in] nSize is the number of observations in pData. [in] argMenthod This parameter is reserved and must be 1. [out] retVal is the computed value.
- Remarks
- 1. The time series may include missing values (NaN), but they will not be included in the calculations.
- 2. The sample mean difference (MD) is computed as follows:
- \[\Delta = \mathrm{MD} = \frac{\sum_{i=1}^n \sum_{j=1}^n \| x_i - x_j \|}{n \times \left ( n-1 \right )}\]
- Where:
- \(x_i\) is the value of the i-th non-missing observation.
- \(n\) is the number of non-missing observations in the sample.
- 4. The mean difference is the product of the sample mean and the relative mean difference (RMD) and so can also be expressed in terms of the NDK_GINI:
- \[\mathrm{MD}= 2 \times G \times \bar{x}\]
- Where:
- \(\bar{x}\) is the arithmetic sample mean.
- \(G\) is the NDK_GINI.
- 6. Because of its ties to the Gini coefficient, the mean difference is also called the "Gini mean difference." It is also known as the "absolute mean difference."
- 7. The sample mean difference is not dependent on a specific measure of central tendency like the standard deviation.
- 8. The mean difference of a sample is an unbiased and consistent estimator of the population mean difference.
- Exceptions
-
Exception Type Condition None N/A
- Requirements
-
Namespace NumXLAPI Class SFSDK Scope Public Lifetime Static Package NumXLAPI.DLL
- Examples
-
- References
- Hull, John C.; Options, Futures and Other DerivativesFinancial Times/ Prentice Hall (2011), ISBN 978-0132777421
