F.L. Bauer has treated in several papers [1, 3, 4] the condition related to the solution of linear equations and to the algebraic eigenvalue problem. We study the condition for the linear least...doi:10.1007/BF01389762Werner Sautter
Seems it can be used in Simulink with 'sqp' or 'sqp-legacy' algorithms. The estimates can be good, but not as good or robust as 'lsqcurvefit'. Might try to find some C code for a non-linear least squares estimator with linear constraints, and implement that directly in...
Linear Least Squares with Bounds and Linear Constraints An algorithm is given for solving linear least squares systems of algebraic equations subject to simple bounds on the unknowns and (more general) linear eq... RJ Hanson - 《Siam Journal on Scientific & Statistical Computing》 被引量: 82发...
This work therefore addresses an overarching question: what technology mixes might provide the least-cost supply of all energy services to a household under increasingly tight emission constraints? Furthermore, this work explores how such an optimal mix may change depending on: i) location-dependent ...
3 stages to implement this subclass base.Model and only calculate parameters, returning a special Results instance that only has params and some information about which constraints are binding. This includes a wrapper about nnls (*1) or slsqp plus the interface adjustments to let user define const...
Thus we only need to perform real arithmetic operation, which is the main advantage of above algorithms. Accordingly, they are very efficient and portable. 5. Numerical examples In this section, we provide two numerical examples to illustrate the efficiency of our algorithms. In the first example...
Note that these constraints are all either linear, of the form c ¼ a = 1 or quadratic, constraining aTCa = 1 where C is a 6 6 constraint matrix. In a seminal work, Bookstein [1] showed that if a quadratic constraint is set on the parameters (e.g., to avoid the trivial ...
In this article, we present aQRupdating procedure as a solution approach for linear least squares problem with equality constraints. We reduce the constrained problem to unconstrained linear least squares and partition it into a small subproblem. TheQRfactorization of the subproblem is calculated and ...
and the constraints are−5≤xi≤5fori=1,…,n. For large enoughn, the dense matrixCdoes not fit into computer memory (n=10,000is too large on one tested system). A Jacobian multiply function has the following syntax. w = jmfcn(Jinfo,Y,flag) ...
"plinear", the Golub-Pereyra algorithm for partially linear least-squares problems; "port", thenls2solalgorithm from thePortlibrary with parameter bounds constraints. External R-packages aimed at nonlinear least squares optimization include the popularminpack.lmpackage or John Nash’snlsrpackage. The...