Sequential Specification Tests to Choose a Model: A Change-Point Approach

Researchers faced with a sequence of candidate model specifications must often choose the best specification that does not violate a testable identification assumption. One option in this scenario is sequential specification tests: hypothesis tests of the identification assumption over the sequence. Borrowing an idea from the change-point literature, this paper shows how to use the distribution of p-values from sequential specification tests to estimate the point in the sequence where the identification assumption ceases to hold. Unlike current approaches, this method is robust to individual errant p-values and does not require choosing a test level or tuning parameter. This paper demonstrates the method's properties with a simulation study, and illustrates it by application to the problems of choosing a bandwidth in a regression discontinuity design while maintaining covariate balance and of choosing a lag order for a time series model

The ring compression test: Analysis of dimensions and canonical geometry

The compression ring test is universally accepted as a perfectly valid method by which determine simply and reliably the adhesion friction factor in a plastic deformation process. Its methodology is based on the application of geometric changes as both the reduction in thickness as the decrease in bore inner diameter in the strained ring itself. In this paper the performance of that test is the basis for establishing the coefficient of friction on a forging process so that, given this, its application to Upper Bound Theorem (UBT) by model Triangular Rigid Zones (TRZ), enable the establishment an intercomparison with empirical force, reaching a cuasivalidation of this Theorem in a certain range.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

A network inference method for large-scale unsupervised identification of novel drug-drug interactions

Characterizing interactions between drugs is important to avoid potentially harmful combinations, to reduce off-target effects of treatments and to fight antibiotic resistant pathogens, among others. Here we present a network inference algorithm to predict uncharacterized drug-drug interactions. Our algorithm takes, as its only input, sets of previously reported interactions, and does not require any pharmacological or biochemical information about the drugs, their targets or their mechanisms of action. Because the models we use are abstract, our approach can deal with adverse interactions, synergistic/antagonistic/suppressing interactions, or any other type of drug interaction. We show that our method is able to accurately predict interactions, both in exhaustive pairwise interaction data between small sets of drugs, and in large-scale databases. We also demonstrate that our algorithm can be used efficiently to discover interactions of new drugs as part of the drug discovery process

1-concave basis for TU games

The first stage of research, twenty years ago, on the subclass of 1-convex TU games dealt with its characterization through some regular core structure. Appealing abstract and practical examples of 1-convex games were missing until now. Both drawbacks are solved. On the one hand, a generating set for the cone of 1-concave cost games is introduced with clear affinities to the unanimity games taking into account the complementary transformation on coalitions. The dividends within this new game representation are used to characterize the 1-concavity constraint as well as to investigate the core property of the Shapley value for cost games. We present a simple formula to compute the nucleolus and the τ-value within the class of 1-convex/1-concave games and show that in a 1-convex/1-concave game there is an explicit relation between the nucleolus and the Shapley value. On the other hand, an appealing practical example of 1-concave cost game has cropped up not long ago in Sales’s Ph.D study of Catalan university library consortium for subscription to journals issued by Kluwer publishing house, the so-called library cost game which turn out to be decomposable into the abstract 1-concave cost games of the generating set mentioned above

Order-parameter fluctuations in Ising spin glasses at low temperatures

We present a numerical study of the order-parameter fluctuations for Ising spin glasses in three and four dimensions at very low temperatures and without an external field. Accurate measurements of two previously introduced parameters, A and G, show that the order parameter is not self-averaging, consistent with a zero-temperature thermal exponent value \theta' \simeq 0, and confirm the validity of the relation G=1/3 in the thermodynamic limit in the whole low-temperature phase, as predicted by stochastic stability arguments.Comment: 7 pages, 7 eps figures, RevTe