Using the syntax described in this topic, you can produce linear regressions in EQL.
| ID | X | Y |
|---|---|---|
| 1 | 60 | 3.1 |
| 2 | 61 | 3.6 |
| 3 | 62 | 3.8 |
| 4 | 63 | 4 |
| 5 | 65 | 4.1 |
The following simple formulation:
y = A + Bx
RETURN Regression AS SELECT
COUNT(ID) AS N,
SUM(X) AS sumX,
SUM(Y) AS sumY,
SUM(X*Y) AS sumXY,
SUM(X*X) AS sumX2,
((N*sumXY)-(sumX*sumY)) /
((N*sumX2)-(sumX*sumX)) AS B,
(sumY-(B*sumX))/N AS A
GROUP
With the result:
| N | sumX | sumY | sumXY | sumX2 | B | A |
|---|---|---|---|---|---|---|
| 5 | 311.000000 | 18.600000 | 1159.700000 | 19359.000000 | 0.187838 | -7.963514 |
DEFINE Regression AS SELECT
COUNT(ID) AS N,
SUM(X) AS sumX,
SUM(Y) AS sumY,
SUM(X*Y) AS sumXY,
SUM(X*X) AS sumX2,
((N*sumXY)-(sumX*sumY)) /
((N*sumX2)-(sumX*sumX)) AS B,
(sumY-(B*sumX))/N AS A
GROUP
RETURN Results AS SELECT
Y AS Y, X AS X, Regression[].A + Regression[].B * X AS Projection
...
As a final step in the example above, you would need to PAGE or GROUP what could be a very large number of results.