# NDK_XKURT

 int __stdcall NDK_XKURT ( double * X, size_t N, WORD reserved, double * retVal )

Calculates the sample excess kurtosis.

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. [in] reserved This parameter is reserved and must be 1. [out] retVal is the calculated sample excess-kurtosis value.
Remarks
1. The data sample may include missing values (e.g. #N/A).
2. Using a given data sample, the sample excess kurtosis is calculated as:
$\hat K (x)= \frac{\sum_{t=1}^T(x_t-\bar x)^4}{(T-1)\hat \sigma^4}-3$,
where:
• $$\hat K(x)$$ is the sample excess kurtosis.
• $$x_i$$ is the i-th non-missing value in the data sample.
• $$T$$ is the number of non-missing values in the data sample.
• $$\hat \sigma$$ is the sample standard deviation.
Requirements
Examples



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

Calculates the sample excess kurtosis.

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. [in] argMenthod This parameter is reserved and must be 1. [out] retVal is the calculated sample excess-kurtosis value.
Remarks
1. The data sample may include missing values (e.g. #N/A).
2. Using a given data sample, the sample excess kurtosis is calculated as:
$\hat K (x)= \frac{\sum_{t=1}^T(x_t-\bar x)^4}{(T-1)\hat \sigma^4}-3$,
where:
• $$\hat K(x)$$ is the sample excess kurtosis.
• $$x_i$$ is the i-th non-missing value in the data sample.
• $$T$$ is the number of non-missing values in the data sample.
• $$\hat \sigma$$ is the sample standard deviation.
Exceptions
Exception Type Condition
None N/A
Requirements
Namespace NumXLAPI SFSDK Public Static NumXLAPI.DLL
Examples

References
Hull, John C.; Options, Futures and Other DerivativesFinancial Times/ Prentice Hall (2011), ISBN 978-0132777421