NDK_RMSE

int __stdcall NDK_RMSE ( double *  X,
double *  Y,
size_t  N,
WORD  retType,
double *  retVal 
)

Calculates the root mean squared error (aka root mean squared deviation (RMSD)) function.

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 original (eventual outcomes) time series sample data (a one dimensional array).
[in] Y is the forecast time series data (a one dimensional array).
[in] N is the number of observations in X.
[in] retType is a switch to select the return output (1=RMSE (default), 2=NRMSE, 3=CV(RMSE)).
[out] retVal is the calculated value of this function.
Remarks
1. The RMSE is also known as root mean squared deviation (RMSD).
2. Please see NDK_RMSD for definition and notes.
Requirements
Header SFSDK.H
Library SFSDK.LIB
DLL SFSDK.DLL
Examples


   
Namespace:  NumXLAPI
Class:  SFSDK
Scope:  Public
Lifetime:  Static
int NDK_RMSE ( double[]   pData1,
double[]   pData2,
UIntPtr  nSize,
short  retType,
ref double  retVal 
)

Calculates the root mean squared error (aka root mean squared deviation (RMSD)) function.

Return Value

a value from NDK_RETCODE enumeration for the status of the call. 

NDK_SUCCESS  operation successful
Error  Error Code
Parameters
[in] pData1 is the original (eventual outcomes) time series sample data (a one dimensional array).
[in] pData2 is the forecast time series data (a one dimensional array).
[in] nSize is the number of observations in X.
[in] retType is a switch to select the return output (1=RMSE (default), 2=NRMSE, 3=CV(RMSE)).
[out] retVal is the calculated value of this function.
Remarks
1. The RMSE is also known as root mean squared deviation (RMSD).
2. Please see NDK_RMSD for definition and notes.
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