In this report we analyze different model selection criteria that were used in statistics, reconstruction, recognition and other areas. We concentrate on criteria based on Bayesian theory, MDL theory, and predicting future residuals. Our analysis showed that these criteria often are not consistent when the number of points in the underlying data of the model is changed or if the scale of the da...

Transaction management is the key component of process-sensitive engineering environments (PSEE). In recent years, several advanced transaction models have been proposed to support long transaction. However, in view of specific characteristic in software process transaction, those models only meet its partial requirements. Moreover, no commercial or academic results of nested cooperative transa...

Model selection is an important part of any statistical analysis, and indeed is central to the pursuit of science in general. Many authors have examined this question, from both frequentist and Bayesian perspectives, and many tools for selecting the \best model" have been suggested in the literature. This paper evaluates the various proposals from a decision{theoretic perspective, as a way of b...

The two most popular model selection rules in the signal processing literature have been the Akaike’s criterion AIC and the Rissanen’s principle of minimum description length MDL. These rules are similar in form in that they both consist of data and penalty terms. Their data terms are identical, but the penalties are different, the MDL being more stringent toward overparameterization. The AIC p...

Model selection is the problem of distinguishing competing models, perhaps featuring different numbers of parameters. The statistics literature contains two distinct sets of tools, those based on information theory such as the Akaike Information Criterion (AIC), and those on Bayesian inference such as the Bayesian evidence and Bayesian Information Criterion (BIC). The Deviance Information Crite...

In this paper, we discuss adjustable coverage criteria and their combinations in model-based testing. We formalize coverage criteria and specify test goals using OCL. Then, we propose a set of functions which describe the test generation process in a generic way. Each coverage criterion is mapped to a set of test goals. Based on this set of functions, we propose a generic framework enabling fle...

Model transformations are core to MDE, and one of the key aspects for all model transformations is that they are validated. In this paper we develop an approach to testing model transformations based on white-box coverage measures of the transformations. To demonstrate the use of this approach we apply it to some examples from the ATL metamodel zoo.

Asymptotic properties of model selection criteria for high-dimensional regression models are studied where the dimension of covariates is much larger than the sample size. Several sufficient conditions for model selection consistency are provided. Non-Gaussian error distributions are considered and it is shown that the maximal number of covariates for model selection consistency depends on the ...

this paper presents a mathematical model for a flow shop scheduling problem consisting of m machine and n jobs with fuzzy processing times that can be estimated as independent stochastic or fuzzy numbers. in the traditional flow shop scheduling problem, the typical objective is to minimize the makespan). however,, two significant criteria for each schedule in stochastic models are: expectable m...