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Goodness of fit measures for revealed preference tests: complexity results and algorithms

机译:揭示偏好测试的拟合优度:复杂度结果和算法

摘要

We provide results on the computational complexity of goodness of fit measures (i.e. Afriat's efficiency index, Varian's efficiency vector-index and the Houtman-Maks index) associated with several revealed preference axioms (i.e. WARP, SARP, GARP and HARP). These results explain the computational difficulties that have been observed in literature when computing these indices. Our NP-Hardness results are obtained by reductions from the independent setproblem. We also show that this reduction can be used to prove that no constant factor approximations algorithm exists for Varian's index, nor for Houtman-Maks' index (unless P = NP). Finally, we give an exact polynomial time algorithm for finding Afriat's efficiency index.
机译:我们提供了一些拟合优度(即Afriat效率指数,Varian效率矢量指数和Houtman-Maks指数)与几种揭示的偏好公理(即WARP,SARP,GARP和HARP)相关的计算复杂性的结果。这些结果解释了在计算这些索引时在文献中已经观察到的计算困难。我们的NP硬度结果是通过减少独立设置问题获得的。我们还表明,这种减少可以用来证明不存在针对Varian指数或Houtman-Maks指数的常数因子近似算法(除非P = NP)。最后,我们给出了精确的多项式时间算法来查找Afriat的效率指标。

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