ESTIMATION OF THE DENSITY AND THE REGRESSION FUNCTION UNDER MIXING CONDITIONS

By Eckhard Liebscher. 2001

85 citations recorded by the source corpus.

Subfields: Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/cc666f5ad6ed764538658d8f563295bfb36b7a0a

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In Mechanics of Materials

1. Pierre-Francois Marteau
2. Valérie Monbet
3. Pierre Ailliot

Citations in the corpus

• Interpolation-based Q-learning (2004, unknown): “kernel density estimators (Liebscher, 2001).”
• Towards a Unified Approach for Proving Geometric Ergodicity and Mixing Properties of Nonlinear Autoregressive Processes (2005, background): “In the field of nonparametric statistics for autoregressive sequences, mixing assumptions play an important role as it is shown in papers byMasry and Tj stheim (1995) and Liebscher (1999, 2001).”
• L1-convergence of smoothing densities in non-parametric state space models (2008, methodology): “Assumptions [K(ζ)]1 and [K(ζ)]2 are common in kernel estimation (see [15]) and [K(ζ)]3 allow us to obtain appropriate convergence rate for the bias and to improve slightly former results, such as those reported in [5].”