| int __stdcall NDK_MAD | ( | double * | X, |
| size_t | N, | ||
| WORD | reserved, | ||
| double * | retVal | ||
| ) |
Returns the sample median of absolute deviation (MAD).
- 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] reserved This parameter is reserved and must be 1. [out] retVal is the calculated value of this function.
- Remarks
- 1. The input data series may include missing values (NaN), but they will not be included in the calculations.
- 2. The median of absolute deviation (MAD) is defined as follows:
- \[\operatorname{MAD} = \operatorname{median}_{i}\left(\ \left| X_{i} - \operatorname{median}_{j} (X_{j}) \right|\ \right)\]
- 3. In short, starting with the deviations from the data's median, the MAD is the median of their absolute values.
- 4. The median of absolute deviation (MAD) is a measure of statistical dispersion.
- 5. MAD is a more robust estimator of scale than the sample variance or standard deviation.
- 6. MAD is especially useful with distributions that have neither mean nor variance (e.g. the Cauchy distribution.)
- 7. MAD is a robust statistic because it is less sensitive to outliers in a data series than standard deviation.
- Requirements
-
Header SFSDK.H Library SFSDK.LIB DLL SFSDK.DLL
- Examples
-
| Namespace: | NumXLAPI |
| Class: | SFSDK |
| Scope: | Public |
| Lifetime: | Static |
| int NDK_MAD | ( | double[] | pData, |
| UIntPtr | nSize, | ||
| short | argMenthod, | ||
| ref double | retVal | ||
| ) |
Returns the sample median of absolute deviation (MAD).
- 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 This parameter is reserved and must be 1. [out] retVal is the calculated value of this function.
- Remarks
- 1. The input data series may include missing values (NaN), but they will not be included in the calculations.
- 2. The median of absolute deviation (MAD) is defined as follows:
- \[\operatorname{MAD} = \operatorname{median}_{i}\left(\ \left| X_{i} - \operatorname{median}_{j} (X_{j}) \right|\ \right)\]
- 3. In short, starting with the deviations from the data's median, the MAD is the median of their absolute values.
- 4. The median of absolute deviation (MAD) is a measure of statistical dispersion.
- 5. MAD is a more robust estimator of scale than the sample variance or standard deviation.
- 6. MAD is especially useful with distributions that have neither mean nor variance (e.g. the Cauchy distribution.)
- 7. MAD is a robust statistic because it is less sensitive to outliers in a data series than standard deviation.
- 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
- Hamilton, J .D.; Time Series Analysis , Princeton University Press (1994), ISBN 0-691-04289-6
