Both intra- and interspecific genomic comparisons have revealed local similarities in the level and frequency of mutational variation, as well as in patterns of gene expression. This autocorrelation between measurements leads to violations of assumptions of independence in many statistical methods, resulting in misleading and incorrect inferences. Here I show that autocorrelation can be due to ...

the classical method of process capability analysis necessarily assumes that collected data are independent; nonetheless, some processes such as biological and chemical processes are autocorrelated and violate the independency assumption. many processes exhibit a certain degree of correlation and can be treated by autoregressive models among which the autoregressive model of order one (ar (1)) ...

  In an increasing number of practical situations, the quality of a process or product can be effectively characterized and summarized by a profile. A profile is usually a functional relationship between a response variable and one or more explanatory variables which can be modeled frequently using linear or nonlinear regression models. In this paper, we study the effect of non-normality on pro...

We present preliminary results of a statistical analysis obtained with a sample of blazars observed at the Perugia Astronomical Observatory since 1992. We briefly show how these statistical results can be useful to discriminate faint variable sources against the background noise. This technique, together with the more traditional ones, may be used to discover and identify high-energy point sour...

Spatial autocorrelation is a method of Exploratory Spatial Data Analysis (ESDA). The latter set of methods allow for the study and understanding of the spatial distribution and spatial structure as well as they allow for detecting spatial dependence or autocorrelation in spatial data. More specifically, spatial autocorrelation is the correlation between the values of a single variable that is s...

Spatial autocorrelation occurs when values of a variable sampled at nearby locations are more similar than those sampled at locations more distant from each other. Spatial autocorrelation can occur at multiple spatial scales or vary with spatial orientation (cardinal direction). It is common in ecological data. In landscape ecology research, scientists often are interested in testing the statis...

In the February 1991 issue of GEOPHYSICS, Anton Ziolkowski gives a scathing criticism of statistical wavelet estimation methods. Among other points, Ziolkowski questions the validity of the randomness assumption. This assumption allows statistical methods to estimate the seismic source wavelet autocorrelation from the seismic trace autocorrelation. In this study, we examine this traditional ass...

In most ecological studies, within-group variation is a nuisance that obscures patterns of interest and reduces statistical power. However, patterns of within-group variability often contain information about ecological processes. In particular, such patterns can be used to detect positive growth autocorrelation (consistent variation in growth rates among individuals in a cohort across time), e...

Accepted 4 April 2008 Copyright © EEF ISSN 1399-1183 Species distributional models based on lattice data often display spatial autocorrelation. Spatial autocorrelation means that observations from nearby locations are often more similar than would be expected on a random basis (Legendre and Legendre 1998). Spatial autocorrelation can arise in both species distributions and environmental variabl...

We define a combined DEA score to evaluate efficiency in agricultural research. The production model we propose considers efficiency measurements under variable returns to scale for each year in the period 2012–2017. We postulate a first-order autoregressive process in the presence of covariates, to explain efficiency. Powers of the autocorrelation coefficient estimated assuming a dynamic panel...