l4P5 (beta-003) | 2009-05-05 20:38 |
Loc (beta-005) | 2009-05-05 20:33 |
wrj4p5 (alpha-011) | 2009-05-05 20:41 |
- *[class] Vfunc 5/20/2008 by Classiclll
- *
- * Model of the Vector Function with parameters
- * f : R^n.R^m -> R
- *
- * can solve the followings with Simplex(Nelder) and Newton
- * for given p, find x such that f(x;p) = 0
- * for given p, find extreme point x* such that f(x*;p)/dx = 0
- * estimate parameters p* such that ssr(obs,samples,p*)/dp = 0
- * based the observations, {obs[i] in R, samples[i] in R^n}
- *
- Vfunc(int domX, int domP) // construct
- // & setup the internal inplementations of EqSys as solver
- int domDim() {return domX;} // dimension of the domain (n)
- int paramDim() {return domP;} // dimension of the params (m)
- abstract double valueAt(Vec x, Vec p) // this parameterized function (R^n.R^m -> R)
- abstract Vec gradAt(Vec x, Vec p) // this gradient arround x, given p
- abstract Vec gradParamAt(Vec x, Vec p) // this gradient arround p, given x
- double valueAt(Vec x) // conbinient method with no parameters.
- Vec gradAt(Vec x) // conbinient method with no parameters.
- Vec diffAt(Vec x, Vec d, Vec p) // gradient estimator at x+d using valueAt()
- Vec diffParamAt(Vec x, Vec d, Vec p)// param grad estimator at p+d using valueAt()
- // 1. for solving the equation of this function.
- private class thisEqSys extends EqSys // an implementation of Equation System
- Vec solveByNewton(Vec x0, Vec p) // find the solution by newton, start at x0
- Vec solveBySimplex(Vec x0, Vec p, int limit) // find the solution by Simplex, start at x0
- // 2. for finding of the extreme point of this function
- private class gradEqSys extends EqSys // an implementation of Equation System
- //find one extreme point, start at x0
- Vec findeExtremeByNewton(Vec x0, Vec p)
- Vec findeExtremeBySimplex(Vec x0, Vec p, int limit)
- Vec findeExtremeBySimplex(Vec x0, Vec p, int limit, int tryal)
- // 3. least sqare equation system based by the Square Sum of Residual
- private class paramEqSys extends EqSys // an implementation of Equation System
- // estimate the params by Least Square Sum
- Vec bestPrmByNewton(Vec p, Vec obs, Mat samples)
- Vec bestPrmBySimplex(Vec p, Vec obs, Mat samples, int limit)
- Vec bestPrmBySimplex(Vec p, Vec obs, Mat samples, int limit, int tryal)
- // the Formulation for the Least Square Sum of the Sum of Square residuals
- double ssrAt(Vec p, Vec obs, Mat samples) //calcurate the Square Sum of Residuals at "p".
- Vec residual(Vec p, Vec obs, Mat samples) // calculate the each residual at "p"
- Vec ssrGradAt(Vec p, Vec obs, Mat samples) // gradient of ssr based gradParamAt()
- Vec ssrJacobAt(Vec p, Vec obs, Mat samples) // jacobian of ssr based gradParamAt()
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更新日時: 2008-08-08 12:03:31, 更新者: classiclll
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