The program LMSMVE performs robust regression analysis by using the method of the least median of squares. It also computes robust distances to locate leverage points. that is. outliers with respect to the set of independent variables. LMSMVE constructs plots of least median of squares residuals aga
A Pascal program for weighted least squares regression on a microcomputer
โ Scribed by H Tyson; H Henderson; M McKenna
- Publisher
- Elsevier Science
- Year
- 1982
- Weight
- 845 KB
- Volume
- 15
- Category
- Article
- ISSN
- 0010-468X
No coin nor oath required. For personal study only.
โฆ Synopsis
Weighted least-squares regression has been programmed in Pascal for a microcomputer. A double precision Pascal compiler and the Motorola 6809 assembler produce a fast machine-code program occupying 22000 bytes of memory when appended to the Pascal run-time module. Large data sets fit in the remaining memory. A regression with 72 observations and 24 parameters runs in 7 min, excluding optional print oat of large matrices. The maximum dimensions of the design matrix, X, can be altered by modifying two Pascal constants. Minor changes to the Pascal source program will make it compatible with other Pascal compilers.
The program optionally orthogonalises the X matrix to detect linearly-dependent columns in X, and/or generate orthogonal parameter estimates. After orthogonalizing X and fitting the model, the parameter estimates for the original X can be retrieved by the program. Regressions on a repea,.edly reduced model are performed through elimination of columns in X until the minimum adequate model is obtained.
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Least-squares regression analysis is widely used in analytical method comparison studies even though model assumptions are typically violated. The advantages favoring the use of the least-squares technique, when applicable, are that its theoretical characteristics are thoroughly developed and the ca