pyacs.lib.robustestimators module¶
RobustEstimators.py includes a number of robust estimators to solve linear problems.
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exception
pyacs.lib.robustestimators.
Error
[source]¶ Bases:
Exception
Base class for exceptions in module robustestimators.py
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exception
pyacs.lib.robustestimators.
UnboundedFunctionError
[source]¶ Bases:
Exception
Exception raised for unbounded objective function.
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pyacs.lib.robustestimators.
Dikin
(A, y, W, eps=0.003)[source]¶ L1-norm estimation of parameters x using the Dikin’s method using Linear optimization in linear model y=Ax+e
- Parameters
A – Model matrix
y – observed values (observation vector)
W – Weight matrix of observables (of DIAGONAL type)
eps – small value for iteration (default: eps = 1e-6)
:return : x,e: vector of estimated parameters and residuals
- Note
translated from Matlab code kindly provided by Amir Khodabandeh june.2009
reference:Recursive Algorithm for L1 Norm Estimation in Linear Models, A. Khodabandeh and A. R. Amiri-Simkooei, JOURNAL OF SURVEYING ENGINEERING ASCE / FEBRUARY 2011 / 1 doi:10.1061/ASCESU.1943-5428.0000031 Translated to python from Matlab original by J.-M. Nocquet July 2011
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pyacs.lib.robustestimators.
Dik_m
(c, A, b, er)[source]¶ subject:solve the standard form of linear programming by affine/Dikin’s method(“an interior point method”) minimize z=c’*x; subject to Ax=b; input:(c):coefficients of objective function(z) as n-vector(hint:a column vector) (A):matrix of constraint set with size m*n (b):m-vector of constraint set (er):maximum discrepancy between two iteration.(“stopping criterion”) output:(X):unknown variables (z):optimal value of objective function (D):Centering transformer “D”(a diagonal matrix) Amir khodabandeh Oct.2008