In recent years, some investigations have been carried out to examine the assumptions like stationarity, symmetry and separability of spatio-temporal covariance function which would considerably simplify fitting a valid covariance model to the data by parametric and nonparametric methods. In this article, assuming a Gaussian random field, we consider the likelihood ratio separability test, a va...

Abstract To avoid the transformation of dependent variable, which introduces bias when back-transformed, complex nonlinear forest models have parameters estimated with heuristic techniques, can supply erroneous values. The solution for accurate provided by Strimbu et al. (Ecosphere 8:e01945, 2017) 11 functions (i.e., power, trigonometric, and hyperbolic) is not based on heuristics but could con...

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 ...