| int __stdcall NDK_TREND | ( | double * | pData, |
| size_t | nSize, | ||
| BOOL | bAscending, | ||
| WORD | nTrendType, | ||
| WORD | argPolyOrder, | ||
| BOOL | AllowIntercep, | ||
| double | InterceptVal, | ||
| int | nHorizon, | ||
| WORD | retType, | ||
| double | argAlpha, | ||
| double * | retVal | ||
| ) |
Returns values along a trend curve (e.g. linear, quadratic, exponential, etc.) at time T+m.
- Returns
- status code of the operation
- Return values
-
NDK_SUCCESS Operation successful NDK_FAILED Operation unsuccessful. See Macros for full list.
- Parameters
-
[in] pData is the univariate time series data (a one dimensional array). [in] nSize is the number of elements in pData. [in] bAscending is the time order in the data series (i.e. the first data point's corresponding date (earliest date=1 (default), latest date=0)). [in] nTrendType is the model description flag for the trend function: Order Description 1 Linear (default) 2 Polynomial 3 Exponential 4 Logarithmic 5 Power [in] argPolyOrder is the polynomial order. This is only relevant for a polynomial trend type and is ignored for all others. If missing, POrder = 1. [in] AllowIntercep is a switch to include or exclude an intercept in the regression. [in] InterceptVal is the constant or the intercept value to fix (e.g. zero). If missing (i.e. NaN), an intercept will not be fixed and is computed normally. [in] nHorizon is the forecast time horizon beyond the end of pData. If missing, a default value of 0 (latest or end of pData) is assumed. [in] retType is a switch to select the return output: Method Description 1 Forecast value (default) 2 C.I. Upper limit 3 C.I. Lower limit 4 R-Squared [in] argAlpha 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 of this function.
- Remarks
-
- NDK_TREND supports the following trend functions: \[ \begin{cases} \mathrm{Linear} & Y_t=\alpha + \beta \times t \\ \mathrm{Polynomial} & Y_t=\alpha + \beta_1 \times t + \beta_2 \times t^2 + \cdots + \beta_N \times t^N \\ \mathrm{Exponential:} & Y_t= \alpha \times e^{\beta \times t} \\ \mathrm{Logarithm:} & Y_t= \alpha + \beta \times \ln(t) \\ \mathrm{Power:} & Y_t= \alpha \times t^{\beta} \\ \end{cases} \]
- For exponential and logarithmic trend in Excel functions, the intercept value is not permitted be fixed, and thus is ignored.
- The polynomial order argument must be a positive integer.
- The time series may include missing values (NaN) at either end.
- Requirements
-
Header SFSDK.H Library SFSDK.LIB DLL SFSDK.DLL
- Examples
-
| Namespace: | NumXLAPI |
| Class: | SFSDK |
| Scope: | Public |
| Lifetime: | Static |
| int NDK_TREND | ( | double[] | pData, |
| int | nSize, | ||
| BOOL | bAscending, | ||
| short | nTrendType, | ||
| short | argPolyOrder, | ||
| BOOL | AllowIntercep, | ||
| double | InterceptVal, | ||
| int | nHorizon, | ||
| short | argRetType, | ||
| double | argAlpha, | ||
| ref double | retVal | ||
| ) |
Returns values along a trend curve (e.g. linear, quadratic, exponential, etc.) at time T+m.
- Returns
- status code of the operation
- Return values
-
NDK_SUCCESS Operation successful NDK_FAILED Operation unsuccessful. See Macros for full list.
- Parameters
-
[in] pData is the univariate time series data (a one dimensional array). [in] nSize is the number of elements in pData. [in] bAscending is the time order in the data series (i.e. the first data point's corresponding date (earliest date=1 (default), latest date=0)). [in] nTrendType is the model description flag for the trend function: Order Description 1 Linear (default) 2 Polynomial 3 Exponential 4 Logarithmic 5 Power [in] argPolyOrder is the polynomial order. This is only relevant for a polynomial trend type and is ignored for all others. If missing, POrder = 1. [in] AllowIntercep is a switch to include or exclude an intercept in the regression. [in] InterceptVal is the constant or the intercept value to fix (e.g. zero). If missing (i.e. NaN), an intercept will not be fixed and is computed normally. [in] nHorizon is the forecast time horizon beyond the end of pData. If missing, a default value of 0 (latest or end of pData) is assumed. [in] argRetType is a switch to select the return output: Method Description 1 Forecast value (default) 2 C.I. Upper limit 3 C.I. Lower limit 4 R-Squared [in] argAlpha 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 of this function.
- Remarks
-
- NDK_TREND supports the following trend functions: \[ \begin{cases} \mathrm{Linear} & Y_t=\alpha + \beta \times t \\ \mathrm{Polynomial} & Y_t=\alpha + \beta_1 \times t + \beta_2 \times t^2 + \cdots + \beta_N \times t^N \\ \mathrm{Exponential:} & Y_t= \alpha \times e^{\beta \times t} \\ \mathrm{Logarithm:} & Y_t= \alpha + \beta \times \ln(t) \\ \mathrm{Power:} & Y_t= \alpha \times t^{\beta} \\ \end{cases} \]
- For exponential and logarithmic trend in Excel functions, the intercept value is not permitted be fixed, and thus is ignored.
- The polynomial order argument must be a positive integer.
- The time series may include missing values (NaN) at either end.
- 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
