Error bounds in cascading regressions
Journal of the International Association for Mathematical Geology
By: M.R. Karlinger and B.M. Troutman
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Abstract
Cascading regressions is a technique for predicting a value of a dependent variable when no paired measurements exist to perform a standard regression analysis. Biases in coefficients of a cascaded-regression line as well as error variance of points about the line are functions of the correlation coefficient between dependent and independent variables. Although this correlation cannot be computed because of the lack of paired data, bounds can be placed on errors through the required properties of the correlation coefficient. The potential meansquared error of a cascaded-regression prediction can be large, as illustrated through an example using geomorphologic data.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Error bounds in cascading regressions |
| Series title | Journal of the International Association for Mathematical Geology |
| DOI | 10.1007/BF01034754 |
| Volume | 17 |
| Issue | 3 |
| Year Published | 1985 |
| Language | English |
| Publisher | Springer |
| Contributing office(s) | Toxic Substances Hydrology Program |
| Description | 9 p. |
| First page | 287 |
| Last page | 295 |
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