Name
Abstract | ||
|---|---|---|
This paper describes several algorithms for computing the residual sums of squares for all possible regressions with what appears to be a minimum of arithmetic (less than six floating-point operations per regression) and shows how two of these algorithms can be combined to form a simple leap and bound technique for finding the best subsets without examining all possible subsets. The result is a reduction of several orders of magnitude in the number of operations required to find the best subsets. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.2307/1271435 | Technometrics |
Keywords | Field | DocType |
floating point,linear regression,sum of squares | Residual,Regression,LEAPS,Statistics,Explained sum of squares,Mathematics,Linear regression | Journal |
Volume | Issue | ISSN |
42 | 1 | 0040-1706 |
Citations | PageRank | References |
60 | 18.90 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| George M. Furnival | 1 | 60 | 18.90 |
| Robert W. Wilson, Jr. | 2 | 60 | 18.90 |