| int __stdcall NDK_GLM_GOF | ( | double * | Y, |
| size_t | nSize, | ||
| double ** | X, | ||
| size_t | nVars, | ||
| double * | betas, | ||
| size_t | nBetas, | ||
| double | phi, | ||
| WORD | Lvk, | ||
| WORD | retType, | ||
| double * | retVal | ||
| ) |
Computes the log-likelihood ((LLF), Akaike Information Criterion (AIC) or other goodness of fit function of the GLM model.
- Returns
- status code of the operation
- Return values
-
NDK_SUCCESS Operation successful NDK_FAILED Operation unsuccessful. See Macros for full list.
- Parameters
-
[in] Y is the response or the dependent variable data array (one dimensional array) [in] nSize is the number of observations [in] X is the independent variables data matrix, such that each column represents one variable [in] nVars is the number of independent variables (or columns in X) [in] betas are the coefficients of the GLM model (a one dimensional array) [in] nBetas is the number of the coefficients in betas. Note that nBetas must be equal to nVars+1 [in] phi is the GLM dispersion parameter. Phi is only meaningful for Binomial (1/batch or trial size) and for Gaussian (variance). - Binomial : phi = Reciprocal of the batch/trial size.
- Gaussian : phi = variance.
- Poisson : phi = 1.0
[in] Lvk is the link function that describes how the mean depends on the linear predictor (see GLM_LINK_FUNC). - Identity (default)
- Log
- Logit
- Probit
- Complementary log-log
[in] retType is a switch to select a fitness measure ( see GOODNESS_OF_FIT_FUNC) [out] retVal is the calculated goodness of fit measure.
- Remarks
-
- The underlying model is described here.
- Missing values (i.e. #N/A!) are not allowed in either the response(Y) or the explanatory input arrays.
- The number of rows in response variable (Y) must be equal to number of rows of the explanatory variables (X).
- The number of betas must equal to the number of explanatory variables (i.e. columns in X) plus one for the intercept.
- For GLM with Poisson distribution,
- The values of response variable must be non-negative integers.
- The value of the dispersion factor (Phi) must be either missing or equal to one.
- For GLM with Binomial distribution,
- The values of the response variable must be non-negative fraction between zero and one, inclusive.
- The value of the dispersion factor (Phi) must be a positive fraction (greater than zero, and less than one).
- For GLM with Gaussian distribution, the dispersion factor (Phi) value must be positive.
- Requirements
-
Header SFSDK.H Library SFSDK.LIB DLL SFSDK.DLL
- 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
