| int __stdcall NDK_GINI | ( | double * | X, |
| size_t | N, | ||
| double * | retVal | ||
| ) |
Returns the sample Gini coefficient, a measure of statistical dispersion.
- 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 (must be non-negative) (a one dimensional array of values). [in] N is the number of observations in X. [out] retVal is the calculated value of this function.
- Remarks
- 1. A low Gini coefficient indicates a more equal distribution, with 0 corresponding to complete equality. Higher Gini coefficients indicate more unequal distributions, with 1 corresponding to complete inequality.
- 2. The input data series may include missing values (NaN), but they will not be included in the calculations.
- 3. The values in the input data series must be non-negative.
- 4. The Gini coefficient is computed as follows:
- \[G(S)=1-\frac{2}{n-1}\left ( n-\frac{\sum_{i=1}^{n}iy_i}{\sum_{i=1}^{n}y_i} \right )\]
- Where:
- \(h\) is the input data series ( \(h\)) arranged in descending order, so that \(y_i\leq y_{i+1}\).
- \(n\) is the number of non-missing values in the input time series data sample.
- NDK_RMD().
- 7. \(G(S)\) is a consistent estimator of the population Gini coefficient, but is generally unbiased (except when the population mean is known).
- 8. Developed by the Italian statistician Corrado Gini in 1912, the Gini coefficient is commonly used as a measure of comparative income or wealth. Where zero (0) corresponds to complete equality and one (1) to complete inequality.
- Requirements
-
Header SFSDK.H Library SFSDK.LIB DLL SFSDK.DLL
- Examples
-
| Namespace: | NumXLAPI |
| Class: | SFSDK |
| Scope: | Public |
| Lifetime: | Static |
| int NDK_GINI | ( | double[] | pData, |
| UIntPtr | nSize, | ||
| ref double | retVal | ||
| ) |
Returns the sample Gini coefficient, a measure of statistical dispersion.
- 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 (must be non-negative) (a one dimensional array of values). [in] nSize is the number of observations in pData. [out] retVal is the calculated value of this function.
- Remarks
- 1. A low Gini coefficient indicates a more equal distribution, with 0 corresponding to complete equality. Higher Gini coefficients indicate more unequal distributions, with 1 corresponding to complete inequality.
- 2. The input data series may include missing values (NaN), but they will not be included in the calculations.
- 3. The values in the input data series must be non-negative.
- 4. The Gini coefficient is computed as follows:
- \[G(S)=1-\frac{2}{n-1}\left ( n-\frac{\sum_{i=1}^{n}iy_i}{\sum_{i=1}^{n}y_i} \right )\]
- Where:
- \(h\) is the input data series ( \(h\)) arranged in descending order, so that \(y_i\leq y_{i+1}\).
- \(n\) is the number of non-missing values in the input time series data sample.
- NDK_RMD().
- 7. \(G(S)\) is a consistent estimator of the population Gini coefficient, but is generally unbiased (except when the population mean is known).
- 8. Developed by the Italian statistician Corrado Gini in 1912, the Gini coefficient is commonly used as a measure of comparative income or wealth. Where zero (0) corresponds to complete equality and one (1) to complete inequality.
- 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
