Ever since the conception of statistical ranking-and-selection (R8S) problem, a predominant approach has been indifference-zone (IZ) formulation. Under IZ formulation, R8S procedures are designed to provide guarantee on probability correct selection (PCS) whenever performance best system exceeds that second-best by specified amount. We discuss shortcomings this and argue providing good (PGS)—se...

In this paper, we propose a semi-parametric model for autonomous nonlinear dynamical systems and devise an estimation procedure for model fitting. This model incorporates subjectspecific effects and can be viewed as a nonlinear semi-parametric mixed effects model. We also propose a computationally efficient model selection procedure. We prove consistency of the proposed estimator under suitable...

Within each simulation study conducted in Section 4 of the manuscript, we also examine the performance of the standard model selection procedures commonly used in the literature; the Bayesian Information Criterion (BIC) (Schwarz, 1978) and the Vuong test (Vuong, 1989). Specifically, we record, according to these model selection methods, which model is selected or if no model is selected at all....

recently several 1,3,4-oxadiazole derivatives were identified as potentially active antimycobacterial agents. various 5-aryl-2-thio-1,3,4-oxadiazoles have been reported having good antimycobacterial activity against mycobacterium tuberculosis h37rv (atcc 27294). in this paper we report 3d qsar studies for the 41 molecules of 1,3,4-oxadiazoles by using k-nearest neighbor molecular field analysis...

 We consider the problem of model selection in vector autoregressive model with Normal innovation. Tests such as Vuong's and Cox's tests are provided for order and model selection, i.e. for selecting the order and a suitable subset of regressors, in vector autoregressive model. We propose a test as a modified log-likelihood ratio test for selecting subsets of regressors. The Europe oil prices, ...

Detection of positive Darwinian selection has become ever more important with the rapid growth of genomic data sets. Recent branch-site models of codon substitution account for variation of selective pressure over branches on the tree and across sites in the sequence and provide a means to detect short episodes of molecular adaptation affecting just a few sites. In likelihood ratio tests based ...

(i .. Can neural network model selection be guided by statistical procedures such as hypothesis tests, information criteria and cross-validation? Recently, Anders and Kom (1999) proposed five neural network model specification strategies based on different statistical procedures. In this paper, we use and adapt the Anders-Koru framework to find appropriate neural network models for financial ti...

Penalized least squares procedures that directly penalize the number of variables in a regression model (L0 penalized least squares procedures) enjoy nice theoretical properties and are intuitively appealing. On the other hand, L0 penalized least squares methods also have significant drawbacks in that implementation is NP-hard and computationally unfeasible when the number of variables is even ...

Many time series exhibit non-stationary behavior, i.e. either their mean or covariances are functions of time. The so-called modulated autoregressive process, an AR process where the variance is allowed to be a function of time, is a model that allows certain forms of non-stationarity to be modeled in a convenient way. For instance, this model has been used for seismic events such as earthquake...

It is common practice in statistical data analysis to perform datadriven variable selection and derive statistical inference from the resulting model. Such inference enjoys none of the guarantees that classical statistical theory provides for tests and confidence intervals when the model has been chosen a priori. We propose to produce valid “post-selection inference” by reducing the problem to ...