|int __stdcall NDK_GLM_FITTED||(||double *||Y,|
[in,out] 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)
- Complementary log-log
[in] retType is a switch to select a output type ( see FIT_RETVAL_FUNC)
- The underlying model is described here.
- GLM_VOL returns an array of size equal to number of rows in the input response (Y) or explanatory variables (X).
- The number of rows in response variable (Y) must be equal to number of rows of the explanatory variables (X).
- The betas input is optional, but if the user provide one, the number of betas must equal to the number of explanatory variables (i.e. X) plus one (intercept).
- For GLM with Poisson distribution,
- The values of response variable must be non-negative integers.
- The value of the dispersion factor (Phi) value must be either missing or equal to one.
- For GLM with Binomial distribution,
- The values of the response variable must be non-negative fractions 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.
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