The Errors-in-Variables context is a challenging environment well known from many years that has seen an increasing amount of research and, consequently, of new results, only in relatively recent times. One of the appealing features of EIV models consists in their intrinsic capability of describing real processes and in relying only on limited sets of a–priori assumptions [24, 25]. These featur...

When model input variables appear redundant, it is common practice to simply drop some of them until the redundancy is removed, prior to model identification. As a result, the final model has forgotten the interdependency in the original input data, which may be an essential condition for

The following sections describe the measurement principle behind the OptiCentric® instruments and typical errors which occur during the assembly of lenses and objectives. The measurement of a centering error primarily involves defining a point of symmetry in relation to a reference axis. This can, for example, be the center of curvature of a lens surface or the location of a focus point of a le...

The purpose of this research study is assessing the relationship between unemployment and its determinants for five east Africa community countries i.e., Kenya, Uganda, Tanzania, Rwanda & Burundi. Particularly, discussed are some economic variables their significant effects especially in long run. include; inflation, GDP growth, population growth foreign direct investments relation to unemp...

one of the models that can be used to study the relationship between boolean random sets and explanatory variables is growth regression model which is defined by generalization of boolean model and permitting its grains distribution to be dependent on the values of explanatory variables. this model can be used in the study of behavior of boolean random sets when their coverage regions variation...