Journal Articleshttp://hdl.handle.net/10453/132014-04-23T11:36:13Z2014-04-23T11:36:13ZIsoelastic oligopolies under uncertaintyChiarella, CarlMatsumoto, AkioSzidarovszky, Ferenchttp://hdl.handle.net/10453/274022014-04-20T18:05:15Z2013-01-01T00:00:00ZIsoelastic oligopolies under uncertainty
Chiarella, Carl; Matsumoto, Akio; Szidarovszky, Ferenc
Single-product oligopolies are examined with uncertain isoelastic price functions and linear cost functions. Each firm wants to maximize its expected profit and also wants to minimize its uncertainty by minimizing the variance. This multiobjective optimization problem is solved by the weighting method, where the utility function of each firm is a linear combination of the expectation and variance of its profit. The existence and uniqueness of the equilibrium of the resulting n-person game is proved and an efficient algorithm is suggested to compute the equilibrium. The asymptotic behavior of the equilibrium is also investigated. Complete stability and bifurcation analysis is presented. The theoretical results are verified by computer simulation.
2013-01-01T00:00:00ZRevisiting the optimal detection of quantum informationChitambar, EricHsieh, Min-Hsiuhttp://hdl.handle.net/10453/270912014-04-14T02:53:17Z2013-01-01T00:00:00ZRevisiting the optimal detection of quantum information
Chitambar, Eric; Hsieh, Min-Hsiu
In 1991, Peres and Wootters wrote a seminal paper on the nonlocal processing of quantum information [Phys. Rev. Lett. 66, 1119 (1991)]. We return to their classic problem and solve it in various contexts. Specifically, for discriminating the 'double trin
2013-01-01T00:00:00ZThe Fractional Clifford-Fourier KernelCraddock, MarkHogan, Johnhttp://hdl.handle.net/10453/270922014-04-14T02:53:17Z2013-01-01T00:00:00ZThe Fractional Clifford-Fourier Kernel
Craddock, Mark; Hogan, John
The Clifford-Fourier transform was introduced by Brackx, De Schepper and Sommen who subsequently computed its kernel in dimension d=2. Here we compute the kernel of a fractional version of the transform when d=2 and 4. In doing so we solve appropriate wa
2013-01-01T00:00:00ZPrior distributions for random choice structuresMccausland, WilliamMarley, Anthonyhttp://hdl.handle.net/10453/270942014-04-14T02:53:17Z2013-01-01T00:00:00ZPrior distributions for random choice structures
Mccausland, William; Marley, Anthony
We study various axioms of discrete probabilistic choice, measuring how restrictive they are, both alone and in the presence of other axioms, given a specific class of prior distributions over a complete collection of finite choice probabilities. We do t
2013-01-01T00:00:00Z