This paper establishes uniform consistency results for nonparametric kernel density and regression estimators when time series regressors concerned are nonstationary null recurrent Markov chains.
In this article, we revisit some problems in non-parametric hypothesis testing. First, we extend the classical result of Bahadur & Savage [Ann. Math. Statist. 25 (1956) 1115] to other testing problems ...
The study of statistical convergence of complex uncertain sequences bridges classical analysis with uncertainty quantification, addressing challenges inherent in systems where outcomes are not ...
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