void
test_quantile(const double p, const double data[], const size_t n,
const double expected, const double tol, const char *desc)
{
gsl_rstat_quantile_workspace *w = gsl_rstat_quantile_alloc(p);
double result;
size_t i;
for (i = 0; i < n; ++i)
gsl_rstat_quantile_add(data[i], w);
result = gsl_rstat_quantile_get(w);
if (fabs(expected) < 1.0e-4)
gsl_test_abs(result, expected, tol, "%s p=%g", desc, p);
else
gsl_test_rel(result, expected, tol, "%s p=%g", desc, p);
gsl_rstat_quantile_free(w);
}
/* add a data point to the running totals */
int
gsl_rstat_add(const double x, gsl_rstat_workspace *w)
{
double delta = x - w->mean;
double delta_n, delta_nsq, term1, n;
/* update min and max */
if (w->n == 0)
{
w->min = x;
w->max = x;
}
else
{
if (x < w->min)
w->min = x;
if (x > w->max)
w->max = x;
}
/* update mean and variance */
n = (double) ++(w->n);
delta_n = delta / n;
delta_nsq = delta_n * delta_n;
term1 = delta * delta_n * (n - 1.0);
w->mean += delta_n;
w->M4 += term1 * delta_nsq * (n * n - 3.0 * n + 3.0) +
6.0 * delta_nsq * w->M2 - 4.0 * delta_n * w->M3;
w->M3 += term1 * delta_n * (n - 2.0) - 3.0 * delta_n * w->M2;
w->M2 += term1;
/* update median */
gsl_rstat_quantile_add(x, w->median_workspace_p);
return GSL_SUCCESS;
} /* gsl_rstat_add() */