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Divide regression weights by stddev instead of minimum distance

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This improves accuracy with large but stable network delays.
This commit is contained in:
Miroslav Lichvar
2010-12-14 17:00:53 +01:00
parent 833022b745
commit c88801065f
1 changed files with 8 additions and 4 deletions
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12
sourcestats.c
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@@ -384,7 +384,7 @@ SST_DoNewRegression(SST_Stats inst)
double est_intercept, est_slope, est_var, est_intercept_sd, est_slope_sd; double est_intercept, est_slope, est_var, est_intercept_sd, est_slope_sd;
int i, j, nruns; int i, j, nruns;
double min_distance; double min_distance;
double sd_weight; double sd_weight, sd;
double old_skew, old_freq, stress; double old_skew, old_freq, stress;
int regression_ok; int regression_ok;
@@ -406,11 +406,15 @@ SST_DoNewRegression(SST_Stats inst)
/* And now, work out the weight vector */ /* And now, work out the weight vector */
sd = sqrt(inst->variance);
if (sd > min_distance || sd <= 0.0)
sd = min_distance;
for (i=0; i<inst->n_samples; i++) { for (i=0; i<inst->n_samples; i++) {
sd_weight = 1.0 + SD_TO_DIST_RATIO * (peer_distances[i] - min_distance) / min_distance; sd_weight = 1.0 + SD_TO_DIST_RATIO * (peer_distances[i] - min_distance) / sd;
weights[i] = sd_weight * sd_weight; weights[i] = sd_weight * sd_weight;
} }
} }
regression_ok = RGR_FindBestRegression(times_back + inst->runs_samples, regression_ok = RGR_FindBestRegression(times_back + inst->runs_samples,
offsets + inst->runs_samples, weights, offsets + inst->runs_samples, weights,