In 2001 Carlsson and Fullér introduced the possibilistic mean value, variance and covariance of fuzzy numbers. In 2002 Fullér and Majlender introduced the notations of crisp weighted possibilistic mean value, variance and covariance of fuzzy numbers, which are consistent with the extension principle. In this paper we will show some (normative) properties of possibility distributions.

In recent years, interest has grown in modeling spatio-temporal data generated from monitoring networks, satellite imaging, and climate models. Under Gaussianity, the covariance function is core to modeling, inference, prediction. this article, we review various space-time structures which simplified assumptions, such as separability full symmetry, are made facilitate computation, associated te...

Methods are developed to establish the limits of statistical uncertainty for values computed from a pair distribution function (PDF) or models fit to a PDF. This is done by computation of a variance-covariance matrix for the PDF from the uncertainties in the diffraction intensities. The application of this variance-covariance matrix also offers optimal weighting for least-squares refinement.

It is well known that there are asymmetric dependence structures between financial returns. This paper describes a portfolio selection method rooted in the classical mean–variance framework incorporates such dependency using nonparametric measure of local dependence, Gaussian correlation (LGC). shown optimization process for returns with straightforward covariance matrices. The new to outperfor...

When information on multiple genotypes evaluated in multiple environments is recorded, a multi-environment single trait model for assessing genotype × environment interaction (G × E) is usually employed. Comprehensive models that simultaneously take into account the correlated traits and trait × genotype × environment interaction (T × G × E) are lacking. In this research, we propose a Bayesian ...

A general observation emerging from estimates of additive genetic variance in sets of functionally or developmentally related traits is that much of the genetic variance is restricted to few trait combinations as a consequence of genetic covariance among traits. While this biased distribution of genetic variance among functionally related traits is now well documented, how it translates to the ...

the present study is an attempt toward evaluating the performance of portfolios and assets selecting using modified mean-variance models by utilizing a non-parametric efficiency analysis tool, namely data envelopment analysis (dea). huge amounts of money are being invested in financial market. as a result, portfolio performance evaluation has created a great deal of interest among people. we kn...

Linear mixed models are often used for the analysis of data from clinical trials with repeated quantitative outcomes. This paper considers linear mixed models where a particular form is assumed for the treatment effect, in particular constant over time or proportional to time. For simplicity, we assume no baseline covariates and complete post-baseline measures, and we model arbitrary mean respo...

Phenotypic integration, the coordinated covariance of suites of morphological traits, is critical for proper functioning of organisms. Angiosperm flowers are complex structures comprising suites of traits that function together to achieve effective pollen transfer. Floral integration could reflect shared genetic and developmental control of these traits, or could arise through pollinator-impose...