Sustainable development is a new concept with various perspectives in communities. Cities and rural areas are in the core of attention for developing. This study focuses on rural areas. Stability of building structures is so important in villages and rural areas. One sustainable development criterion of villagers is suitable housing. In this research, both new and traditional technologies are i...

ABSTRACT In the present paper, we consider the variable selection problem in Poisson regression models. Akaike’s information criterion (AIC) is the most commonly applied criterion for selecting variables. However, the bias of the AIC cannot be ignored, especially in small samples. We herein propose a new bias-corrected version of the AIC that is constructed by stochastic expansion of the maximu...

In order to obtain better generalization performance in supervised learning, model parameters should be determined appropriately, i.e., they should be determined so that the generalization error is minimized. However, since the generalization error is inaccessible in practice, the model parameters are usually determined so that an estimator of the generalization error is minimized. The regulari...

Information criteria have been popularly used in model selection and proved to possess nice theoretical properties. For classification, Claeskens et al. (2008) proposed support vector machine information criterion for feature selection and provided encouraging numerical evidence. Yet no theoretical justification was given there. This work aims to fill the gap and to provide some theoretical jus...

The Akaike Information Criterion can be a valuable tool of scientific inference. This statistic, or any other statistical method for that matter, cannot, however, be the whole of scientific methodology. In this paper some of the limitations of Akaikean statistical methods are discussed. It is argued that the full import of empirical evidence is realized only by adopting a richer ideal of empiri...

The Bayesian information criterion (BIC) is a model selection criterion that has previously been applied to speaker segmentation of broadcast news by several researchers. The BIC approach treats speaker segmentation as a model selection problem. As the BIC requires the estimation of the sample covariance matrix, its performance tends to deteriorate as the speaker-turn duration decreases. It is ...

Feature selection is an essential problem in many fields such as computer vision. In this paper we introduce a supervised feature selection criterion based on Partial Least Squares regression (PLS). We find an optimal feature subset by applying the theory of Optimal Experiment Design to optimize the eigenvalues of the loadings matrix obtained from PLS. Since PLS extracts components such that th...

In the present study, we consider the selection of model selection criteria for multivariate ridge regression. There are several model selection criteria for selecting the ridge parameter in multivariate ridge regression, e.g., the Cp criterion and the modified Cp (MCp) criterion. We propose the generalized Cp (GCp) criterion, which includes Cp andMCp criteria as special cases. The GCp criterio...

We consider the properties of the highest posterior probability model in a linear regression setting+ Under a spike and slab hierarchy we find that although highest posterior model selection is total risk consistent, it possesses hidden undesirable properties+ One such property is a marked underfitting in finite samples, a phenomenon well noted for Bayesian information criterion ~BIC! related p...