Structural reanalysis methods have been proposed to improve the efficiency of structural analysis. However, are typically only applicable their specific type modification. Since optimization process often involves multiple types modifications, it is necessary establish a criterion for selecting most suitable method each modification, aiming accelerate process. In this study, effects different m...

Model selection is commonly based on some variation of the BIC or minimum message length criteria, such as MML and MDL. In either case the criterion is split into two terms: one for the model (data code length/model complexity) and one for the data given the model (message length/data likelihood). For problems such as change detection, unsupervised segmentation or data clustering it is common p...

0 n −1 s t Suppose that there is some true model which generated our time series data, x , . . . , x . Thi rue model is not AR. But we do want to consider using AR models to describe our data, since they a f provide a flexible, estimable, and interpretable class of models. Although the AR models have only ew parameters, the true model presumably has a huge number of parameters (perhaps inf init...

Rank aggregation is an important task in many areas, nevertheless, none of rank aggregation algorithms is best for all cases. The main goal of this work is to develop a method, which for a given rank list finds the best rank aggregation algorithm with respect to a certain optimality criterion. Two approaches based on meta-feature description are proposed and one of them shows promising results.

\Ve show thaI, H.daptive n�al time dyrmmic prograrnming ex­ tended with the action selection strategy which chooses the best action Recording 1.0 the laLest, estimaLe orLhf' cos!' rllndiofl yields i-\..'i.yrnptoLicl-tlly 0pLirnal poli(:ies within riniLe Limp lJnder· !,lIP minimax 0pLirnality criu-'­ rian. H'om this it follows that learning and exploitation do not confiict under this special opt...

The Neighbor-Joining (NJ) method of Saitou and Nei is the most widely used distance based method in phylogenetic analysis. Central to the method is the selection criterion, the formula used to choose which pair of objects to amalgamate next. Here we analyze the NJ selection criterion using an axiomatic approach. We show that any selection criterion that is linear, permutation equivariant, stati...

Kernel selection is a fundamental problem of kernel methods. Existing measures for kernel selection either provide less theoretical guarantee or have high computational complexity. In this paper, we propose a novel kernel selection criterion based on a newly defined spectral measure of a kernel matrix, with sound theoretical foundation and high computational efficiency. We first show that the s...

Process modeling by means of Gaussian-based algorithms often suffers from redundant information which usually increases the estimation computational complexity without significantly improving the estimation performance. In this article, a non-arbitrary measurement selection criterion for Gaussian-based algorithms is proposed. The measurement selection criterion is based on the determination of ...

To compute norms from reference group test scores, continuous norming is preferred over traditional norming. A suitable continuous norming approach for continuous data is the use of the Box-Cox Power Exponential model, which is found in the generalized additive models for location, scale, and shape. Applying the Box-Cox Power Exponential model for test norming requires model selection, but it i...

Previous divide-and-conquer segmentation analyses of DNA sequences do not provide a satisfactory stopping criterion for the recursion. This paper proposes that segmentation be considered as a model selection process. Using the tools in model selection, a limit for the stopping criterion on the relaxed end can be determined. The Bayesian information criterion, in particular, provides a much more...