Titlebook: Limit Theorems for Markov Chains and Stochastic Properties of Dynamical Systems by Quasi-Compactness; Hubert Hennion,Lo?c Hervé Book 2001

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Peripheral Eigenvalues of Fourier Kernels,1 for . are simple. However the conditions .[.] in Section 11.2 only state the simplicity of 1. Besides, the proofs of Theorems B and C require a more precise control of the eigenvalues of greatest modulus for .(.) than the one obtained in Lemma IVA. These remarks motivate the study of this chapter.

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Markov Chains Associated With Lipschitz Kernels Examples,n VIL1) and the large deviations theorem (Theorem E, Section VIII.1) apply to a.Markov chain associated with a general Lipschitz kernel. We then consider the special cases of Lipschitz kernels associated with products of invertible or positive random matrices and with autoregressive stochastic proce

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0075-8434 applied quasi-compact positive Q, obtaining Markov chains for stochastic of or dynamical by describing properties systems, of Perron- Frobenius has been demonstrated in several All use a operator, papers. these works share the features the features that must be same specific general ; used in each s

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Book 2001 Markov chains for stochastic of or dynamical by describing properties systems, of Perron- Frobenius has been demonstrated in several All use a operator, papers. these works share the features the features that must be same specific general ; used in each stem from the nature of the functional parti

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Markov Chains Associated With Lipschitz Kernels Examples,der the special cases of Lipschitz kernels associated with products of invertible or positive random matrices and with autoregressive stochastic processes. Recall that typical instances of Lipschitz kernels have been given in Examples 11.4 and 11.6.

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