It is common practice in statistical data analysis to perform data-driven 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...

Organizations use broadcast search to identify new avenues of innovation. Research on innovation contests provides insights on why excellent ideas are created in a broadcast search. However, there is little research on how excellent ideas are selected. Drawing from the brainstorming literature we find that the selection of excellent ideas needs further investigation. We propose that a hybrid mo...

General unrestricted models (GUMs) may include important individual determinants, many small relevant effects, and irrelevant variables. Automatic model selection procedures can handle perfect collinearity and more candidate variables than observations, allowing substantial dimension reduction from GUMs with salient regressors, lags, non-linear transformations, and multiple location shifts, tog...

We have developed a new approach for preoperative selection of points from a surface model for rigid shape-based registration. This approach is based on an extension of our earlier spatial-stiffness model of fiducial registration. We compared our approach with the maximization of the noise-amplification index (NAI), using target registration accuracy (TRE) as our comparison measure, on models d...

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 ...

Classical step-by-step algorithms, such as forward selection (FS) and stepwise (SW) methods, are computationally suitable, but yield poor results when the data contain outliers and other contaminations. Robust model selection procedures, on the other hand, are not computationally efficient or scalable to large dimensions, because they require the fitting of a large number of submodels. Robust a...

one of the main principles of the passive defense is the principle of site selection. in this paper, we propose a multiple objective nonlinear programming model that considers the principle of the site selection in terms of two qualitative and quantitative aspects. the purpose of the proposed model is selection of the place of facilities of a system in which not only it observes the dispersion ...

Background: Telomeres are particular sequences of DNA located at the end of the eukaryotic chromosomes that are essential for genome integrity. Telomere length in spermatozoa differs among males, as well as spermatozoa. Also, decreased telomere length in spermatozoa of infertile men is associated with the reduction of fertility potential and embryo quality. Density gradient centrifugation (DGC)...

One of the main principles of the passive defense is the principle of site selection. In this paper, we propose a multiple objective nonlinear programming model that considers the principle of the site selection in terms of two qualitative and quantitative aspects. The purpose of the proposed model is selection of the place of facilities of a system in which not only it observes the dispersion ...