1 /* PSPP - a program for statistical analysis.
2 Copyright (C) 2008 Free Software Foundation, Inc.
4 This program is free software: you can redistribute it and/or modify
5 it under the terms of the GNU General Public License as published by
6 the Free Software Foundation, either version 3 of the License, or
7 (at your option) any later version.
9 This program is distributed in the hope that it will be useful,
10 but WITHOUT ANY WARRANTY; without even the implied warranty of
11 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
12 GNU General Public License for more details.
14 You should have received a copy of the GNU General Public License
15 along with this program. If not, see <http://www.gnu.org/licenses/>. */
18 Create and update the values in the covariance matrix.
22 #include <data/variable.h>
23 #include <data/value.h>
24 #include "covariance-matrix.h"
28 The covariances are stored in a DESIGN_MATRIX structure.
30 struct design_matrix *
31 covariance_matrix_create (int n_variables, const struct variable *v_variables[])
33 return design_matrix_create (n_variables, v_variables, (size_t) n_variables);
36 void covariance_matrix_destroy (struct design_matrix *x)
38 design_matrix_destroy (x);
42 Update the covariance matrix with the new entries, assuming that V1
43 is categorical and V2 is numeric.
46 covariance_update_categorical_numeric (struct design_matrix *cov, double mean,
47 double weight, double ssize, const struct variable *v1,
48 const struct variable *v2, const union value *val1, const union value *val2)
55 assert (var_is_alpha (v1));
56 assert (var_is_numeric (v2));
58 row = design_matrix_var_to_column (cov, v1);
59 col = design_matrix_var_to_column (cov, v2);
60 for (i = 0; i < cat_get_n_categories (v1); i++)
63 x = -1.0 * cat_get_n_categories (v1) / ssize;
64 if (i == cat_value_find (v1, val1))
68 assert (val2 != NULL);
69 gsl_matrix_set (cov->m, row, col, (val2->f - mean) * x * weight);
73 column_iterate (struct design_matrix *cov, const struct variable *v, double weight,
74 double ssize, double x, const union value *val1, size_t row)
81 col = design_matrix_var_to_column (cov, v);
82 for (i = 0; i < cat_get_n_categories (v) - 1; i++)
85 y = -1.0 * cat_get_category_count (i, v) / ssize;
86 tmp_val = cat_subscript_to_value (i, v);
87 if (compare_values (tmp_val, val1, var_get_width (v)))
91 gsl_matrix_set (cov->m, row, col, x * y * weight);
92 gsl_matrix_set (cov->m, col, row, x * y * weight);
96 Call this function in the second data pass. The central moments are
97 MEAN1 and MEAN2. Any categorical variables should already have their
98 values summarized in in its OBS_VALS element.
100 void covariance_pass_two (struct design_matrix *cov, double mean1, double mean2,
101 double weight, double ssize, const struct variable *v1,
102 const struct variable *v2, const union value *val1, const union value *val2)
108 union value *tmp_val;
110 if (var_is_alpha (v1))
112 if (var_is_numeric (v2))
114 covariance_update_categorical_numeric (cov, mean2, weight, ssize, v1,
119 row = design_matrix_var_to_column (cov, v1);
120 for (i = 0; i < cat_get_n_categories (v1) - 1; i++)
123 x = -1.0 * cat_get_category_count (i, v1) / ssize;
124 tmp_val = cat_subscript_to_value (i, v1);
125 if (compare_values (tmp_val, val1, var_get_width (v1)))
129 column_iterate (cov, v1, weight, ssize, x, val1, row);
130 column_iterate (cov, v2, weight, ssize, x, val2, row);
134 else if (var_is_alpha (v2))
136 covariance_update_categorical_numeric (cov, mean1, weight, ssize, v2,
142 Both variables are numeric.
144 row = design_matrix_var_to_column (cov, v1);
145 col = design_matrix_var_to_column (cov, v2);
146 x = (val1->f - mean1) * (val2->f - mean2) * weight;
147 gsl_matrix_set (cov->m, row, col, x);
148 gsl_matrix_set (cov->m, col, row, x);