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#ifndef LOGISTIC_H_ /* Include guard */
#define LOGISTIC_H_
// Mixed interface.
void logistic_mixed_pred(gsl_vector *beta, // Vector of parameters
// length = 1+Sum_k(C_k-1)+Kc.
gsl_matrix_int *X, // Matrix Nobs x K.
gsl_vector_int *nlev, // Vector with num. categories.
gsl_matrix *Xc, // Continuous covariates matrix
// Nobs x Kc
gsl_vector *yhat); // Vector of prob. predicted by
// the logistic.
int logistic_mixed_fit(gsl_vector *beta, // Vector of parameters
// length = 1+Sum_k(C_k-1)+Kc
gsl_matrix_int *X, // Matrix Nobs x K.
gsl_vector_int *nlev, // Vector with number categories.
gsl_matrix *Xc, // Continuous covariates
// matrix Nobs x Kc
gsl_vector *y, // Vector of prob. to predict.
double lambdaL1, // Reg. L1 0.0 if not used.
double lambdaL2); // Reg. L2 0.0 if not used.
double fLogit_mixed(gsl_vector *beta,
gsl_matrix_int *X,
gsl_vector_int *nlev,
gsl_matrix *Xc, // continuous covariates matrix Nobs x Kc
gsl_vector *y,
double lambdaL1,
double lambdaL2);
// Categorical-only interface.
void logistic_cat_pred(gsl_vector *beta, // Vector of parameters length = 1 + Sum_k(C_k - 1) + Kc
gsl_matrix_int *X, //Matrix Nobs x K
gsl_vector_int *nlev, // Vector with number categories
gsl_vector *yhat); //Vector of prob. predicted by the logistic
int logistic_cat_fit(gsl_vector *beta, // Vector of parameters length = 1 + Sum_k(C_k - 1) + Kc
gsl_matrix_int *X, //Matrix Nobs x K
gsl_vector_int *nlev, // Vector with number categories
gsl_vector *y, //Vector of prob. to predict
double lambdaL1, // Regularization L1 0.0 if not used
double lambdaL2); // Regularization L2 0.0 if not used
double fLogit_cat(gsl_vector *beta,
gsl_matrix_int *X,
gsl_vector_int *nlev,
gsl_vector *y,
double lambdaL1,
double lambdaL2);
/* Continuous only interface */
void logistic_cont_pred(gsl_vector *beta // Vector of parameters length = 1 + Sum_k(C_k - 1) + Kc
,gsl_matrix *Xc // continuous covariates Matrix Nobs x Kc
,gsl_vector *yhat //Vector of prob. predicted by the logistic
);
int logistic_cont_fit(gsl_vector *beta // Vector of parameters length = 1 + Sum_k(C_k - 1) + Kc
,gsl_matrix *Xc // continuous covariates Matrix Nobs x Kc
,gsl_vector *y //Vector of prob. to predict
,double lambdaL1 // Regularization L1 0.0 if not used
,double lambdaL2); // Regularization L2 0.0 if not used
double fLogit_cont(gsl_vector *beta,
gsl_matrix *Xc, // Continuous covariates matrix Nobs x Kc .
gsl_vector *y,
double lambdaL1,
double lambdaL2);
#endif // LOGISTIC_H_
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