Map comparison methods are used to express the similarity between maps. They are amongst others used in validation and calibration procedures of spatial models. It is found that traditional map comparison methods do not distinguish small differences from large differences, which leads to comparison results that are not in accordance with human judgment. In this paper a relatively new method for...

Several practical problems of hypotheses testing can be under a general linear model analysis of variance which would be examined. In analysis of variance, when the response random variable Y , has linear relationship with several random variables X, another important model as analysis of covariance can be used. In this paper, assuming that Y is fuzzy and using DLR metric, a method for testing ...

The Fuzzy Kappa statistic expresses the agreement between two categorical raster maps. The statistic goes beyond cell-by-cell comparison and gives partial credit to cells based on the categories found in the neighborhood. When matching categories are found at shorter distances the agreement is higher. Like the well-established Kappa statistic the Fuzzy Kappa statistic expresses the mean agreeme...

This article addresses the fuzziness in regression models. The goal is to present a test procedure to explicitly examine whether an independent variable has a clear functional relationship with the dependent variable in a specific regression model, or whether their relationship is fuzzy. To this end, we interpret the spread of the regression coefficients as a statistic measuring the fuzziness o...

Partitioning a digital circuit into modules before implementing on a single chip is key to balancing between test cost and test correctness of built-in current testing (BICT). Most partitioning methods use statistic analysis to find the threshold value and then to determine the size of a module. These methods are rigid and inflexible since IDDQ testing requires the measurement of an analog quan...