in this work we deal with the coefficients of a (e it ) 2 , where a is in a class of polynomialshaving unimodular coefficients. we first present a technique that calculates lower bounds for particularautocorrelations and then in a more general case we present an upper bound for their maximal order.

  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...

introduction in 1950s, only 30% of the world's population lived in urban areas. by 2000, that proportion increasedup to 47%, and by 2050 the estimated number will be around 72%. urban sprawl, an undesirable type of urban growth, is one of the major concerns ofthe city planners and administrators. understanding urban patterns, dynamic processes, and their relationships is a primary objectiv...

The purpose of this article is to evaluate the application of forecasting models along with the use of residual control charts to assess production processes whose samples have autocorrelation characteristics. The main objective is to determine the efficiency of control charts for individual observations (CCIO) and exponentially weighted moving average (EWMA) charts when they are applied to res...

Physical or geographic location proves to be an important feature in many data science models, because diverse natural and social phenomenon have a spatial component. Spatial autocorrelation measures the extent which locally adjacent observations of same are correlated. Although statistics like Moran’s I Geary’s C widely used measure autocorrelation, they slow: All popular methods run $$\Omega ...