
arXiv: 1107.1144
A permanental vector is a generalization of a vector with components that are squares of the components of a Gaussian vector, in the sense that the matrix that appears in the Laplace transform of the vector of Gaussian squares is not required to be either symmetric or positive definite. In addition the power of the determinant in the Laplace transform of the vector of Gaussian squares, which is -1/2, is allowed to be any number less than zero. It was not at all clear what vectors are permanental vectors. In this paper we characterize all permanental vectors in $R^{3}_{+}$ and give applications to permanental vectors in $R^{n}_{+}$ and to the study of permanental processes.
Statistics and Probability, M-matrices, Markov processes, Applied Mathematics, Probability (math.PR), Infinitely divisible distributions; stable distributions, permanental vectors, Infinitely divisible vectors, Characteristic functions; other transforms, Stochastic processes, Modelling and Simulation, FOS: Mathematics, Gaussian squares, Mathematics - Probability, Permanental vectors, infinitely divisible vectors
Statistics and Probability, M-matrices, Markov processes, Applied Mathematics, Probability (math.PR), Infinitely divisible distributions; stable distributions, permanental vectors, Infinitely divisible vectors, Characteristic functions; other transforms, Stochastic processes, Modelling and Simulation, FOS: Mathematics, Gaussian squares, Mathematics - Probability, Permanental vectors, infinitely divisible vectors
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