criterion performance measurements

overview

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eigenvalues

lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 1.7385457472413e-8 1.835031013982965e-8 2.025594657565993e-8
Standard deviation 3.1282790812486034e-9 4.693710776331409e-9 7.461582394405134e-9

Outlying measurements have severe (0.9889248635851954%) effect on estimated standard deviation.

singularValues

lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 1.6826225845589296e-8 1.7946005660116075e-8 2.0023645512318482e-8
Standard deviation 3.8065732744977515e-9 5.086762617501991e-9 6.7528119439801565e-9

Outlying measurements have severe (0.9891478561960904%) effect on estimated standard deviation.

svd

lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 1.6221274055690446e-8 1.7234160259299247e-8 1.8475294982447158e-8
Standard deviation 2.4881510946468646e-9 3.4964843827801714e-9 5.242763712903595e-9

Outlying measurements have severe (0.9818072866034199%) effect on estimated standard deviation.

thin svd

lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 1.5200992008592096e-8 1.6036688852170936e-8 1.762968570110854e-8
Standard deviation 3.0315150245405474e-9 3.82028582129978e-9 5.2817180591673615e-9

Outlying measurements have severe (0.9854833619936364%) effect on estimated standard deviation.

nullspace

lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 2.5508530956636188e-8 2.723408409043705e-8 2.9744327114652017e-8
Standard deviation 4.680099577947827e-9 6.313600629360875e-9 9.050556218313498e-9

Outlying measurements have severe (0.9850256799098543%) effect on estimated standard deviation.

orthogonal

lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 2.0414364374562542e-8 2.475013778281937e-8 3.954756017309537e-8
Standard deviation 5.50738164362259e-9 2.2818323488591064e-8 4.632165338530646e-8

Outlying measurements have severe (0.9965008367265807%) effect on estimated standard deviation.

determinant

lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 2.0255712720735736e-8 2.285106190872731e-8 2.9551073305864862e-8
Standard deviation 8.195782543629916e-9 1.2221105180713979e-8 1.9597216160046445e-8

Outlying measurements have severe (0.9963771382744843%) effect on estimated standard deviation.

understanding this report

In this report, each function benchmarked by criterion is assigned a section of its own. The charts in each section are active; if you hover your mouse over data points and annotations, you will see more details.

Under the charts is a small table. The first two rows are the results of a linear regression run on the measurements displayed in the right-hand chart.

We use a statistical technique called the bootstrap to provide confidence intervals on our estimates. The bootstrap-derived upper and lower bounds on estimates let you see how accurate we believe those estimates to be. (Hover the mouse over the table headers to see the confidence levels.)

A noisy benchmarking environment can cause some or many measurements to fall far from the mean. These outlying measurements can have a significant inflationary effect on the estimate of the standard deviation. We calculate and display an estimate of the extent to which the standard deviation has been inflated by outliers.