The paper considers quantile-wavelet estimation for time-varying coefficients by embedding a wavelet kernel into quantile regression. Our methodology is quite general in the sense that we do not require unknown to be smooth curves of common degree or errors independently distributed. Quantile-wavelet robust outliers heavy-tailed data. model dynamic nonlinear time series. A strong Bahadur order ...

This paper is about the homogenization of linear elliptic operators in divergence form with stationary random coefficients that have only slowly decaying correlations. It deduces optimal estimates error from growth (extended) corrector. In line heuristics, there are transitions at dimension $d=2$, and for a correlation-decay exponent $\beta=2$; we capture correct power logarithms coming these t...

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