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| author | Pjotr Prins | 2017-07-07 06:54:26 +0000 |
|---|---|---|
| committer | Pjotr Prins | 2017-07-07 06:54:26 +0000 |
| commit | b9758364059d52e153a9f1b4fcae3bc3f3e68422 (patch) | |
| tree | cc3b526c1621ca452ded085114d7c40559c09887 /src/logistic.h | |
| parent | dd72b87354d1d3f6d3aa42ed0123a23880e9cb15 (diff) | |
| download | pangemma-b9758364059d52e153a9f1b4fcae3bc3f3e68422.tar.gz | |
Fix spacing
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 |