# NDK_IQR

 int __stdcall NDK_IQR ( double * X, size_t N, double * retVal )

Returns the inter quartile range (IQR), also called the mid-spread or middle fifty.

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 dimensional array). [in] N is the number of observations in X. [out] retVal is the calculated IQR value.
Note
1. The input time series data may include missing values (NaN), but they will not be included in the calculations.
2. The interquartile range is defined as follows:
$\mathrm{IQR}=Q_3-Q_1$
where
• $$Q_3$$ is the third quartile.
• $$Q_1$$ is the first quartile.
3. Interquartile range (IQR) is a robust statistic because it has a break down point of 25%. It is often preferred to the total range.
Requirements
Examples



 Namespace: NumXLAPI Class: SFSDK Scope: Public Lifetime: Static
 int NDK_IQR ( double[] pData, UIntPtr nSize, ref double retVal )

Returns the inter quartile range (IQR), also called the mid-spread or middle fifty.

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 dimensional array). [in] nSize is the number of observations in pData. [out] retVal is the calculated IQR value.
Remarks
1. The input time series data may include missing values (NaN), but they will not be included in the calculations.
2. The interquartile range is defined as follows:
$\mathrm{IQR}=Q_3-Q_1$
where
• $$Q_3$$ is the third quartile.
• $$Q_1$$ is the first quartile.
3. Interquartile range (IQR) is a robust statistic because it has a break down point of 25%. It is often preferred to the total range.
Exceptions
Exception Type Condition
None N/A
Requirements
Namespace NumXLAPI SFSDK Public Static 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