This paper proposes a new spatial lag regression model which addresses global autocorrelation arising from cross-sectional dependence between counts. Our approach offers an intuitive interpretation of the correlation parameter as measurement impact neighbouring observations on conditional expectation It allows for flexible likelihood-based inference based different distributional assumptions us...

In this correspondence, we will point out a problem with testing adaptive classifiers on autocorrelated data. In such a case random change alarms may boost the accuracy figures. Hence, we cannot be sure if the adaptation is working well.

Many problems do not have one or more variables that determine quality characteristics. In these situations, as a solution method, profile is descibed by linking independent to the response variable. One of common assumptions in most monitoring schemes assumption residuals. Contravention this can lead misleading results control chart. On other hand, when data are contaminated, classical methods...

This research aims to present a literature review (LR) on control charts for autocorrelated processes, intending contribute the scientific knowledge of process management area. The article was constructed having question defined ex-ante, elaborated based literature, where protocol adapted from Tranfield, Denyer, and Smart (2003) systematized according methodological rigor demanded in review, wh...

A new method for estimating divergence times when evolutionary rates are variable across lineages is proposed. The method, called nonparametric rate smoothing (NPRS), relies on minimization of ancestor-descendant local rate changes and is motivated by the likelihood that evolutionary rates are autocorrelated in time. Fossil information pertaining to minimum and/or maximum ages of nodes in a phy...