2.4 KiB
2.4 KiB
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statsmodels.linearRegression() function | `statsmodels.linearRegression()` performs a linear regression. |
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301 |
statsmodels.linearRegression()
performs a linear regression.
It calculates and returns ŷ (y_hat
),
and residual sum of errors (rse
).
Output data includes the following columns:
- N: Number of points in the calculation.
- slope: Slope of the calculated regression.
- sx: Sum of x.
- sxx: Sum of x squared.
- sxy: Sum of x*y.
- sy: Sum of y.
- errors: Residual sum of squares.
Defined by
(r.y - r.y_hat) ^ 2
in this context - x: An index [1,2,3,4...n], with the assumption that the timestamps are regularly spaced.
- y: Field value
- y_hat: Linear regression values
Function type signature
(
<-tables: stream[A],
) => stream[{
B with
y_hat: float,
y: float,
x: float,
sy: H,
sxy: G,
sxx: F,
sx: E,
slope: D,
errors: float,
N: C,
}] where A: Record, D: Divisible + Subtractable
{{% caption %}} For more information, see Function type signatures. {{% /caption %}}
Parameters
tables
Input data. Default is piped-forward data (<-
).
Examples
Perform a linear regression on a dataset
import "contrib/anaisdg/statsmodels"
import "sampledata"
sampledata.float()
|> statsmodels.linearRegression()