Loess
Edit this pageThe loess transform (for locally-estimated scatterplot smoothing) uses locally-estimated regression to produce a trend line. Loess performs a sequence of local weighted regressions over a sliding window of nearest-neighbor points. For standard parametric regression options, see the regression transform.
// Any View Specification
{
...
"transform": [
{"loess": ...} // Loess Transform
...
],
...
}
Loess Transform Definition
Property | Type | Description |
---|---|---|
loess | String |
Required. The data field of the dependent variable to smooth. |
on | String |
Required. The data field of the independent variable to use a predictor. |
groupby | String[] |
The data fields to group by. If not specified, a single group containing all data objects will be used. |
bandwidth | Number |
A bandwidth parameter in the range Default value: |
as | String[] |
The output field names for the smoothed points generated by the loess transform. Default value: The field names of the input x and y values. |
Usage
{"loess": "y", "on": "x", "bandwidth": 0.5}
Generate a loess trend line that models field "y"
as a function of "x"
, using a bandwidth parameter of 0.5
. The output data stream can then be visualized with a line mark, and takes the form:
[
{"x": 1, "y": 2.3},
{"x": 2, "y": 2.9},
{"x": 3, "y": 2.7},
...
]
If the groupby
parameter is provided, separate trend lines will be fit per-group, and the output records will additionally include all groupby field values.