Description Usage Arguments Details Value Author(s) References Examples
Lagrange multipliers allows to give a analytic solution for equality constrained least squares problem (LSE).
1 |
A |
Design matrix, m rows and n columns. |
C |
Constraint matrix, p rows and n columns. |
b |
Response vector for A, Ax=b, m rows and 1 column. |
d |
Response vector for C, Cx=d, p rows and 1 column. |
The Lagrange multipliers method gives a numerical vector as the solution of a least squares problem (Ax=b) through unification the model and their restrictions in one function, the restrictions impose in the model (additional information, extramuestral information or a priori information) lead to another linear equality system (Cx=d). See significance constraint (x=0) or inclusion restriction (x+y=1), etc.
Numerical vector for a LSE problem.
Sergio Andrés Cabrera Miranda Statician sergio05acm@gmail.com
Rao, C. R., Toutenburg, H., Shalabh, H. C., & Schomaker, M. (2008). Linear models and generalizations. Least Squares and Alternatives (3rd edition) Springer, Berlin Heidelberg New York.
Theil, H. (1971). Principles of econometrics (No. 04; HB139, T44.).
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