StochaTR
swMATH ID:  11113 
Software Authors:  Bazovkin, P.; Mosler, K. 
Description:  Stochastic linear programming with a distortion risk constraint. Coherent distortion risk measures are applied to capture the possible violation of a restriction in linear optimization problems whose parameters are uncertain. Each risk constraint induces an uncertainty set of coefficients, which is proved to be a weightedmean trimmed region. Thus, given a sample of the coefficients, an uncertainty set is a convex polytope that can be exactly calculated. We construct an efficient geometrical algorithm to solve stochastic linear programs that have a single distortion risk constraint. The algorithm is available as an Rpackage. The algorithm’s asymptotic behavior is also investigated, when the sample is i.i.d. from a general probability distribution. Finally, we present some computational experience. 
Homepage:  http://www.insider.org/packages/cran/StochaTR 
Dependencies:  R 
Related Software:  Qhull; R; modQR; ddalpha; fda.usc; OjaNP; CompPD; mrfDepth; depth; depth.plot; moQuantile; DepthProc; geometry; Octave; TukeyRegion; locfit; Rglpk; rgl; UCIml; robustbase 
Cited in:  7 Documents 
Standard Articles
1 Publication describing the Software, including 1 Publication in zbMATH  Year 

Stochastic linear programming with a distortion risk constraint. Zbl 1305.90321 Mosler, Karl; Bazovkin, Pavel 
2014

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Cited by 9 Authors
4  Mosler, Karl Clemens 
3  Mozharovskyi, Pavlo 
2  Bazovkin, Pavel 
1  den Hertog, Dick 
1  Dyckerhoff, Rainer 
1  Liu, Xiaohui 
1  Melenberg, Bertrand 
1  Postek, Krzysztof 
1  Zuo, Yijun 
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Cited in 6 Serials
2  Statistical Science 
1  Annals of Operations Research 
1  SIAM Review 
1  Computational Statistics and Data Analysis 
1  OR Spectrum 
1  Journal of Computational and Graphical Statistics 
Cited in 4 Fields
5  Statistics (62XX) 
3  Operations research, mathematical programming (90XX) 
1  Convex and discrete geometry (52XX) 
1  Game theory, economics, finance, and other social and behavioral sciences (91XX) 