# NDK_PROBIT

 int __stdcall NDK_PROBIT ( double * X, size_t N, WORD retTYpe )

Computes the probit transformation, including its inverse.

Returns
status code of the operation
Return values
 NDK_SUCCESS Operation successful NDK_FAILED Operation unsuccessful. See Macros for full list.
Parameters
 [in,out] X is the univariate time series data (a one dimensional array). [in] N is the number of observations in X. [in] retTYpe is a number that determines the type of return value: 1 (or missing)=probit , 2=inverse probit.
Remarks
1. The probit link function is commonly used for parameters that lie in the unit interval.
2. Numerical values of X close to 0 or 1 or out of range result in #VALUE! or #N/A.
3. The probit function is defined as the inverse cumulative distribution function (CDF): $y=\textit{Probit}(x)=\Phi^{-1}(x)$ And $x=\textit{probit}^{-1}(y)=\Phi(y)=\frac{1}{\sqrt{2\pi}}\int_{-\infty}^{y}e^{\frac{-Z^2}{2}}dz$ Where:
• $$x_{t}$$ is the value of the input time series at time $$t$$
• $$y_{t}$$ is the transformed probit value at time $$t$$
• $$\textit{probit}^{-1}(y)$$ is the inverse probit function
4. The probit function accepts a single value or an array of values for X.
Requirements
Examples

 Namespace: NumXLAPI Class: SFSDK Scope: Public Lifetime: Static

 int NDK_PROBIT ( double[] pData, UIntPtr nSize, short argRetType )

Computes the probit transformation, including its inverse.

Returns
status code of the operation
Return values
 NDK_SUCCESS Operation successful NDK_FAILED Operation unsuccessful. See Macros for full list.

Parameters
 [in,out] pData is the univariate time series data (a one dimensional array). [in] nSize is the number of observations in pData. [in] argRetType is a number that determines the type of return value: 1 (or missing)=probit , 2=inverse probit.
Remarks
1. The probit link function is commonly used for parameters that lie in the unit interval.
2. Numerical values of X close to 0 or 1 or out of range result in #VALUE! or #N/A.
3. The probit function is defined as the inverse cumulative distribution function (CDF): $y=\textit{Probit}(x)=\Phi^{-1}(x)$ And $x=\textit{probit}^{-1}(y)=\Phi(y)=\frac{1}{\sqrt{2\pi}}\int_{-\infty}^{y}e^{\frac{-Z^2}{2}}dz$ Where:
• $$x_{t}$$ is the value of the input time series at time $$t$$
• $$y_{t}$$ is the transformed probit value at time $$t$$
• $$\textit{probit}^{-1}(y)$$ is the inverse probit function
4. The probit function accepts a single value or an array of values for X.
Exceptions
Exception Type Condition
None N/A
Requirements
Namespace NumXLAPI SFSDK Public Static NumXLAPI.DLL
Examples
References
* John H. Aldrich, Forrest D. Nelson; Linear Probability, Logit, and Probit Models; SAGE Publications, Inc; 1st Edition(Nov 01, 1984), ISBN: 0803921330
* 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