summary
Description
summary(
displays the multiple
test correction drift status and the summary of the drift diagnostics returned by the
DDiagnostics
)detectdrift
function.
returns the table S
= summary(DDiagnostics
)S
containing the summary of the drift diagnostic
results.
Examples
Display Summary of Drift Diagnostics
Generate baseline and target data with two variables, where the distribution parameters of the second variable change for target data.
rng('default') % For reproducibility baseline = [normrnd(0,1,100,1),wblrnd(1.1,1,100,1)]; target = [normrnd(0,1,100,1),wblrnd(1.2,2,100,1)];
Perform permutation testing for any drift between the baseline and the target data.
DDiagnostics = detectdrift(baseline,target);
Display the summary of the drift diagnostics.
summary(DDiagnostics)
Multiple Test Correction Drift Status: Drift DriftStatus PValue ConfidenceInterval ___________ ______ ______________________ x1 "Stable" 0.285 0.25719 0.31408 x2 "Drift" 0.003 0.0006191 0.008742
summary
displays the multiple test correction drift status above the summary table. detectdrift
uses the default multiple test correction method, Bonferroni, which determines that the drift status for the overall data is Drift
. The summary table has two rows, one for each variable, and three columns containing the drift status, estimated p-value, and 95% confidence bounds for the estimated p-values. detectdrift
identifies the drift status as stable for the first variable, and detects the drift in the distribution for the second variable. The upper confidence bound for the second variable is lower than the default drift threshold of 0.05, so the drift status for this variable is Drift
.
Save Summary of Drift Diagnostics
Generate baseline and target data with two variables, where the distribution parameters of the second variable change for the target data.
rng('default') % For reproducibility baseline = [normrnd(0,1,100,1),wblrnd(1.1,1,100,1)]; target = [normrnd(0,1,100,1),wblrnd(1.2,2,100,1)];
Perform permutation testing for any drift between the baseline and target data.
DDiagnostics = detectdrift(baseline,target);
Save the summary of the drift diagnostics in the table S
.
S = summary(DDiagnostics)
S=3×3 table
DriftStatus PValue ConfidenceInterval
___________ ______ ______________________
x1 "Stable" 0.285 0.25719 0.31408
x2 "Drift" 0.003 0.0006191 0.008742
MultipleTest "Drift" NaN NaN NaN
When you save the results in a table, summary
stores the multiple test correction drift status in a row MultipleTest
below the variables. The multiple test correction has no p-value or confidence interval, so the function stores NaN
s.
If you set EstimatePValues
to false in the call to detectdrift
, the software does not perform any estimation or confidence interval computation. In this case, S
stores the name and initial value of the metric you specify for each variable in the call to detectdrift
.
DDiagnostics = detectdrift(baseline,target,EstimatePValues=false); S = summary(DDiagnostics)
S=2×2 table
MetricValue Metric
___________ _____________
x1 0.22381 "Wasserstein"
x2 0.36879 "Wasserstein"
Input Arguments
DDiagnostics
— Diagnostics of permutation testing for drift detection
DriftDiagnostics
object
Diagnostics of the permutation testing for drift detection, specified as a DriftDiagnostics
object returned by detectdrift
.
Output Arguments
S
— Summary of drift diagnostic results
table
Summary of the drift diagnostic results, returned as a table. By default,
S
includes a row for each variable specified for drift detection
in the call to detectdrift
, and a row for the multiple test drift
status, MultipleTest
. In this case, S
has the
following columns.
Column Name | Description |
---|---|
DriftStatus | Drift status at the end of the permutation testing: Drift, Warning, or Stable |
PValue | Estimated p-values |
ConfidenceInterval | Confidence intervals for the estimated p-values |
If you set the value of EstimatePValues
to
false
in the call to detectdrift
, then
S
does not have the row MultipleTest
, and the
number of rows in S
is equal to the number of variables specified
for drift detection. In this case, S
has the following columns.
Column Name | Description |
---|---|
MetricValue | Value of the metric used in permutation testing |
Metric | Metric used in permutation testing |
Version History
Introduced in R2022a
See Also
detectdrift
| DriftDiagnostics
| plotDriftStatus
| plotEmpiricalCDF
| plotPermutationResults
| plotHistogram
| ecdf
| histcounts
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