Central limit theorems for sequential and random intermittent dynamical systems

Abstract

We establish self-norming central limit theorems for non-stationary time series arising as observations on sequential maps possessing an indifferent fixed point. These transformations are obtained by perturbing the slope in the Pomeau-Manneville map. We also obtain quenched central limit theorems for random compositions of these maps.

References in corpus (2)

• Mixing rates and limit theorems for random intermittent maps
• Quasistatic dynamics with intermittency

Cited by in corpus (14)

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• Doubly Intermittent Full Branch Maps with Critical Points and Singularities
• Sunklodas' approach to normal approximation for time-dependent dynamical systems
• Central limit theorems with a rate of convergence for time-dependent intermittent maps
• Random Composition of L-S-V Maps Sampled Over Large Parameter Ranges
• On the law of the iterated logarithm for continued fractions with sequentially restricted partial quotients
• Deviations from Gaussianity in deterministic discrete time dynamical systems
• The Emergence of the Normal Distribution in Deterministic Chaotic Maps
• Stable laws for random dynamical systems