tab_float (tbl, col + 3,
row,
TAB_CENTER,
- m->stderr,
+ m->se_mean,
8,3);
tab_float (tbl, col + 2,
row + 1,
TAB_CENTER,
- m->mean - t * m->stderr,
+ m->mean - t * m->se_mean,
8,3);
tab_text (tbl, col + 1,
tab_float (tbl, col + 2,
row + 2,
TAB_CENTER,
- m->mean + t * m->stderr,
+ m->mean + t * m->se_mean,
8,3);
tab_text (tbl, col,
/* Detrended Normal Plot */
struct chart dnp_chart;
- const struct weighted_value *wv = *(m->wvp);
-
-
/* The slope and intercept of the ideal normal probability line */
const double slope = 1.0 / m->stddev;
const double intercept = - m->mean / m->stddev;
chart_write_xlabel(&dnp_chart, _("Observed Value"));
chart_write_ylabel(&dnp_chart, _("Dev from Normal"));
- yfirst = gsl_cdf_ugaussian_Pinv (wv[0].rank / ( m->n + 1));
- ylast = gsl_cdf_ugaussian_Pinv (wv[m->n_data-1].rank / ( m->n + 1));
+ yfirst = gsl_cdf_ugaussian_Pinv (m->wvp[0]->rank / ( m->n + 1));
+ ylast = gsl_cdf_ugaussian_Pinv (m->wvp[m->n_data-1]->rank / ( m->n + 1));
{
/* Need to make sure that both the scatter plot and the ideal fit into the
double d_min = DBL_MAX;
for ( i = 0 ; i < m->n_data; ++i )
{
- const double ns = gsl_cdf_ugaussian_Pinv (wv[i].rank / ( m->n + 1));
+ const double ns = gsl_cdf_ugaussian_Pinv (m->wvp[i]->rank / ( m->n + 1));
- chart_datum(&np_chart, 0, wv[i].v.f, ns);
+ chart_datum(&np_chart, 0, m->wvp[i]->v.f, ns);
- d_data[i] = (wv[i].v.f - m->mean) / m->stddev - ns;
+ d_data[i] = (m->wvp[i]->v.f - m->mean) / m->stddev - ns;
if ( d_data[i] < d_min ) d_min = d_data[i];
if ( d_data[i] > d_max ) d_max = d_data[i];
chart_rounded_tick((d_max - d_min) / 5.0));
for ( i = 0 ; i < m->n_data; ++i )
- chart_datum(&dnp_chart, 0, wv[i].v.f, d_data[i]);
+ chart_datum(&dnp_chart, 0, m->wvp[i]->v.f, d_data[i]);
free(d_data);
}