Although for the purposes of creating a covariance matrix, only
n - 1 entries are needed, for other purposes (such as descriptive
statistics, contrasts, planned comparisons etc) all n entries are required.
(where n is the number of distinct values). This change updates
categories.c so that all n categories are generated. Covariance matrix
routines are free to ignore the ones not of interest.
printf ("\nReverse variable map:\n");
printf ("\nReverse variable map:\n");
- for (v = 0 ; v < cat->n_cats_total - cat->n_vars; ++v)
+ for (v = 0 ; v < cat->n_cats_total; ++v)
printf ("%d ", cat->reverse_variable_map[v]);
printf ("\n");
}
printf ("%d ", cat->reverse_variable_map[v]);
printf ("\n");
}
int v;
int idx = 0;
cat->reverse_variable_map = pool_calloc (cat->pool,
int v;
int idx = 0;
cat->reverse_variable_map = pool_calloc (cat->pool,
- cat->n_cats_total - cat->n_vars,
sizeof *cat->reverse_variable_map);
for (v = 0 ; v < cat->n_vp; ++v)
sizeof *cat->reverse_variable_map);
for (v = 0 ; v < cat->n_vp; ++v)
}
/* Populate the reverse variable map.
}
/* Populate the reverse variable map.
- This implementation considers the first value of each categorical variable
- as the basis. Therefore, this loop starts from 1 instead of 0 */
- for (i = 1; i < vp->n_cats; ++i)
+ */
+ for (i = 0; i < vp->n_cats; ++i)
cat->reverse_variable_map[idx++] = v;
}
cat->reverse_variable_map[idx++] = v;
}
{
assert (cat->reverse_variable_map);
assert (subscript >= 0);
{
assert (cat->reverse_variable_map);
assert (subscript >= 0);
- assert (subscript < cat->n_cats_total - cat->n_vars);
+ assert (subscript < cat->n_cats_total);
return cat->reverse_variable_map[subscript];
}
return cat->reverse_variable_map[subscript];
}