ee.Reducer.linearRegression
Creates a reducer that computes a linear least squares regression with numX independent variables and numY dependent variables.
Each input tuple will have values for the independent variables followed by the dependent variables.
The first output is a coefficients array with dimensions (numX, numY); each column contains the coefficients for the corresponding dependent variable. The second output is a vector of the root mean square of the residuals of each dependent variable. Both outputs are null if the system is underdetermined, e.g., the number of inputs is less than or equal to numX.
| Usage | Returns |
|---|
ee.Reducer.linearRegression(numX, numY) | Reducer |
| Argument | Type | Details |
|---|
numX | Integer | The number of input dimensions. |
numY | Integer, default: 1 | The number of output dimensions. |
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Last updated 2024-07-13 UTC.
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