Predictive Inference for the Elliptical Linear Model

Predictive Inference Post Model

We give a finite-sample analysis of predictive inference procedures after model selection in regression with random design. The analysis is focused on a statistically challenging scenario where the number of potentially important explanatory variables can be infinite, where no regularity conditions are imposed on unknown parameters, where the number of explanatory variables in a “good” model ca...

Permutation inference for the general linear model

Permutation methods can provide exact control of false positives and allow the use of non-standard statistics, making only weak assumptions about the data. With the availability of fast and inexpensive computing, their main limitation would be some lack of flexibility to work with arbitrary experimental designs. In this paper we report on results on approximate permutation methods that are more...

the use of appropriate madm model for ranking the vendors of mci equipments using fuzzy approach

abstract nowadays, the science of decision making has been paid to more attention due to the complexity of the problems of suppliers selection. as known, one of the efficient tools in economic and human resources development is the extension of communication networks in developing countries. so, the proper selection of suppliers of tc equipments is of concern very much. in this study, a ...

Quantile-based inference for elliptical distributions

We estimate the parameters of an elliptical distribution by means of a multivariate extension of the Method of Simulated Quantiles (MSQ) of Dominicy and Veredas (2010). The multivariate extension entails the challenge of the construction of a function of quantiles that is informative about the covariation parameters. The interquantile range of a projection of pairwise random variables onto the ...

Model Based Predictive Control for Linear Systems