diff options
Diffstat (limited to 'src/logistic.h')
| -rw-r--r-- | src/logistic.h | 150 |
1 files changed, 75 insertions, 75 deletions
diff --git a/src/logistic.h b/src/logistic.h index 7f9e133..b61ab14 100644 --- a/src/logistic.h +++ b/src/logistic.h @@ -1,75 +1,75 @@ -#ifndef LOGISTIC_H_ -#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 if not used - double lambdaL2); // Regularization L2, 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 cov's 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 cov's matrix Nobs x Kc. - gsl_vector *y, // Vector of prob. to predict. - double lambdaL1, // Regularization L1, 0 if not used. - double lambdaL2); // Regularization L2, 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 +#ifndef LOGISTIC_H_ +#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 if not used + double lambdaL2); // Regularization L2, 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 cov's 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 cov's matrix Nobs x Kc. + gsl_vector *y, // Vector of prob. to predict. + double lambdaL1, // Regularization L1, 0 if not used. + double lambdaL2); // Regularization L2, 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 |