NDK_REGRESSION

int __stdcall NDK_REGRESSION ( double *  X,
size_t  nX,
double *  Y,
size_t  nY,
WORD  nRegressType,
WORD  POrder,
double  intercept,
double  target,
WORD  nRetType,
double  alpha,
double *  retVal 
)

calculates the value of the regression function for an intermediate x-value.

Returns
status code of the operation
Return values
NDK_SUCCESS  Operation successful
NDK_FAILED  Operation unsuccessful. See Macros for full list.
Remarks
  1. NxTrend supports the following trend functions: \begin{cases} \mathrm{Linear} & Y=\alpha + \beta \times X \\ \mathrm{Polynomial} & Y=\alpha + \beta_1 \times X + \beta_2 \times X^2 + \cdots + \beta_N \times X^N \\ \mathrm{Exponential:} & Y= \alpha \times e^{\beta \times X} \\ \mathrm{Logarithm:} & Y= \alpha + \beta \times \ln(X) \\ \mathrm{Power:} & Y= \alpha \times X^{\beta} \\ \end{cases}
  2. For exponential and logarithmic trends, the intercept value is not permitted to be fixed, and thus is ignored.
  3. The Excel trend built-in function (i.e. "TREND") is a different function, not part of NumXL, and should not be confused with NxTrend.
  4. The polynomial order argument must be a positive integer.
  5. The trend function's coefficients that best fit your data are estimated using the "least squares" method.
  6. The time series may include missing values (e.g. #N/A) at either end.
Parameters
[in] X is the x-component of the input data table (a one dimensional array).
[in] nX is the number of elements in X.
[in] Y is the y-component (i.e. function) of the input data table (a one dimensional array).
[in] nY is the number of elements in Y
[in] nRegressType is the model description flag for the trend function (1 = Linear (default), 2 = Polynomial, 3 = Exponential, 4 = Logarithmic, 5 = Power).
[in] POrder is the polynomial order. This is only relevant for a polynomial type of trend and is ignored for all others. If missing, POrder = 1.
[in] intercept is the constant or the intercept value to fix (e.g. zero). If missing (NaN), an intercept will not be fixed and is computed normally.
[in] target is the desired x-value to calculate regression value for (a single value).
[in] nRetType is a switch to select the return output (1 = Forecast value (default), 2 = Upper limit, 3 = Lower Limit, 4 = R-Squared).
[in] alpha is the statistical significance or confidence level (i.e. alpha). If missing or omitted, an alpha value of 5% is assumed
[out] retVal is the calculated value
Requirements
Header SFSDK.H
Library SFSDK.LIB
DLL SFSDK.DLL
Namespace:  NumXLAPI
Class:  SFSDK
Scope:  Public
Lifetime:  Static
NDK_REGRESSION ( double  X,
UIntPtr  nX,
double[]  Y,
UIntPtr  nY,
short  nRegressType,
short  POrder,
double  intercept,
double  target,
UInt16  nRetType,
double  alpha,
ref double  retVal 
)

calculates the value of the regression function for an intermediate x-value.

Return Value

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

NDK_SUCCESS  operation successful
Error  Error Code
Remarks
  1. NxTrend supports the following trend functions: \begin{cases} \mathrm{Linear} & Y=\alpha + \beta \times X \\ \mathrm{Polynomial} & Y=\alpha + \beta_1 \times X + \beta_2 \times X^2 + \cdots + \beta_N \times X^N \\ \mathrm{Exponential:} & Y= \alpha \times e^{\beta \times X} \\ \mathrm{Logarithm:} & Y= \alpha + \beta \times \ln(X) \\ \mathrm{Power:} & Y= \alpha \times X^{\beta} \\ \end{cases}
  2. For exponential and logarithmic trends, the intercept value is not permitted to be fixed, and thus is ignored.
  3. The Excel trend built-in function (i.e. "TREND") is a different function, not part of NumXL, and should not be confused with NxTrend.
  4. The polynomial order argument must be a positive integer.
  5. The trend function's coefficients that best fit your data are estimated using the "least squares" method.
  6. The time series may include missing values (e.g. #N/A) at either end.
Parameters
[in] X is the x-component of the input data table (a one dimensional array).
[in] nX is the number of elements in X.
[in] Y is the y-component (i.e. function) of the input data table (a one dimensional array).
[in] nY is the number of elements in Y
[in] nRegressType is the model description flag for the trend function (1 = Linear (default), 2 = Polynomial, 3 = Exponential, 4 = Logarithmic, 5 = Power).
[in] POrder is the polynomial order. This is only relevant for a polynomial type of trend and is ignored for all others. If missing, POrder = 1.
[in] intercept is the constant or the intercept value to fix (e.g. zero). If missing (NaN), an intercept will not be fixed and is computed normally.
[in] target is the desired x-value to calculate regression value for (a single value).
[in] nRetType is a switch to select the return output (1 = Forecast value (default), 2 = Upper limit, 3 = Lower Limit, 4 = R-Squared).
[in] alpha is the statistical significance or confidence level (i.e. alpha). If missing or omitted, an alpha value of 5% is assumed
[out] retVal is the calculated value
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