Regression
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Regression

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Robust trend

FunctionDescriptionExample
robust_trend()Fit a robust regression trend line using Huber loss.robust_trend(avg:<METRIC_NAME>{*})

The most common type of linear regression—ordinary least squares (OLS)—can be heavily influenced by a small number of points with extreme values. Robust regression is an alternative method for fitting a regression line; it is not influenced as strongly by a small number of extreme values. As an example, see the following plot.

The original metric is shown as a solid blue line. The purple dashed line is an OLS regression line, and the yellow dashed line is a robust regression line. The one short-lived spike in the metric leads to the OLS regression line trending upward, but the robust regression line ignores the spike and does a better job fitting the overall trend in the metric.

Trend line

FunctionDescriptionExample
trend_line()Fit an ordinary least squares regression line through the metric values.trend_line(avg:<METRIC_NAME>{*})

Example:

If we draw the function sin(x) * x/2 + x then trend_line(sin(x) * x/2 + x) would have the following shape:

Piecewise constant

FunctionDescriptionExample
piecewise_constant()Approximate the metric with a piecewise function composed of constant-valued segments.piecewise_constant(avg:<METRIC_NAME>{*})

Example:

If we draw the function x then piecewise_constant(x) would have the following shape:

Other functions