The study of statistical convergence of complex uncertain sequences bridges classical analysis with uncertainty quantification, addressing challenges inherent in systems where outcomes are not ...

This paper establishes uniform consistency results for nonparametric kernel density and regression estimators when time series regressors concerned are nonstationary null recurrent Markov chains.

We analyse the performance of a recursive Monte Carlo method for the Bayesian estimation of the static parameters of a discrete-time state-space Markov model. The algorithm employs two layers of ...

For each gene, we characterised the distribution of sequence convergence between pairs of branches in the species phylogeny following the approach described by Castoe et al. (2009) implemented in the ...