Bayesian Model Averaging and Weighted Average Least Squares: Equivariance, Stability, and Numerical Issues

This article is concerned with the estimation of linear regression models with uncertainty about the choice of the explanatory variables. We introduce the Stata commands bma and wals which implement, respectively, the exact Bayesian Model Averaging (BMA) estimator and the Weighted Average Least Squares (WALS) estimator developed by Magnus et al. (2010). Unlike standard pretest estimators which are based on some preliminary diagnostic test, these model averaging estimators provide a coherent way of making inference on the regression parameters of interest by taking into account the uncertainty due to both the estimation and the model selection steps. Special emphasis is given to a number practical issues that users are likely to face in applied work: equivariance to certain transformations of the explanatory variables, stability, accuracy, computing speed and out-of-memory problems. Performances of our bma and wals commands are illustrated using simulated data and empirical applications from the literature on model averaging estimation.Model uncertainty;Model averaging;Bayesian analysis;Exact computation

Planning and managing rural recreational traffic flows: why the future can’t be more like the past

The increasing popularity of rural tourism can cause traffic related problems at certain areas. Traffic congestion and parking problems are likely to occur as the infrastructure at these countryside destinations is seldom capable of dealing with the growing number of cars. Values which make the sites attractive to visitors can become under pressure and car traffic can also have negative effects on natural values. To prevent for such impacts, recreational traffic management is required. Recreational traffic management focuses on a smart organisation of recreational traffic flows. It has developed since the 1970s and to-day its character is influencing. Influencing takes place by offering tempting alternative opportunities and packages with varied facilities, based on specific desires of individual recreants. This requires detailed data on recreational use as well as an actor analysis, both on a regional and local scale

Nano-apatite/polymer composites: mechanical and physicochemical characteristics

Hydrothermally synthesized acicular nano-apatite (Nap) was used as filler to make composites with a polyethylene glycol/poly(butylene terephthalate) (PEG/PBT) block copolymer (Polyactive™70:30). The Nap had a particle diameter of 9–25 nm and a length of 80–200 nm. The mechanical properties and the physiochemical characteristics of the composites, such as Young's modulus, swelling degree in water and the calcification behaviour, have been determined. It was found that Nap had a strong ability to promote the calcification of composites when incorporated into Polyactive 70:30, while poly(acrylic acid) (PAA) coating of Nap had an adverse effect on the calcification of composites, presumably due to the formation of complexes between PAA and PEG segments. Nap had a prominent stiffening effect for Polyactive 70:30 in the dry state, but had a poor stiffening effect for composites in an aqueous environment due to the hygroscopic nature and/or the formation of aggregates. PAA coating on Nap had almost no additional effect on the mechanical properties of composites either in the dry state or in an aqueous environment. To reinforce the polymer by Nap, achieving a more homogeneous dispersion of Nap in the polymer matrix and surface modifications to render the powders less hygroscopic appear to be necessary

Evaluation of porous ceramic cathode layers for solid oxide fuel cells

Sr0.15La0.85MnO3 layers with 2 and 10 u thickness, deposited on zirconia based electrolytes, were evaluated as cathodes for high temperature applications. Different electrode layers were characterized in terms of thickness, porosity, three phase boundary line per unit area (TPBL), and concentration polarization behavior. Electrodes with maximum porosity and TPBL exhibit minimum concentration polarization losses at constant current density

Bug Hunting with False Negatives Revisited

Safe data abstractions are widely used for verification purposes. Positive verification results can be transferred from the abstract to the concrete system. When a property is violated in the abstract system, one still has to check whether a concrete violation scenario exists. However, even when the violation scenario is not reproducible in the concrete system (a false negative), it may still contain information on possible sources of bugs. Here, we propose a bug hunting framework based on abstract violation scenarios. We first extract a violation pattern from one abstract violation scenario. The violation pattern represents multiple abstract violation scenarios, increasing the chance that a corresponding concrete violation exists. Then, we look for a concrete violation that corresponds to the violation pattern by using constraint solving techniques. Finally, we define the class of counterexamples that we can handle and argue correctness of the proposed framework. Our method combines two formal techniques, model checking and constraint solving. Through an analysis of contracting and precise abstractions, we are able to integrate overapproximation by abstraction with concrete counterexample generation

Evaluating Style Analysis

In this paper we evaluate applications of (return based) style analysis.The portfolio and positivity constraints imposed by style analysis are useful in constructing mimicking portfolios without short positions.Such mimicking portfolios can be used, e.g., to construct efficient portfolios of mutual funds with desired factor loadings if the factor loadings in the underlying factor model are positively weighted portfolios.Under these conditions style analysis may also be used to determine a benchmark portfolio for performance measurement. Attribution of the returns on portfolios of which the actual composition is unobserved to speciffic asset classes on the basis of return based style analysis is attractive if moreover there are no additional cross exposures between the asset classes and if fund managers hold securities that on average have a beta of one relative to their own asset class.If such restrictions are not met, and in particular if the factor loadings do not generate a positively weighted portfolio, the restrictions inherent in return based style analysis distort the outcomes of standard regression approaches rather than that the analysis is improved.The size of the distortions is illustrated by considering empirical results on style analysis of US mutual funds.mutual funds;style analysis

Incorporating Estimation Risk in Portfolio Choice

We propose an adjustment in mean-variance portfolio weights to incorporate uncertainty caused by the fact that, in general, we have to use estimated expected returns.The adjustment amounts to using a higher pseudo risk-aversion rather than the actual risk-aversion.The difference between the actual and the pseudo risk-aversion depends on the sample size, the number of assets in the portfolio, and the curvature of the mean-variance frontier.Applying the adjustment to international portfolios, we show that the adjustments are nontrivial for G5 country portfolios and that they are even more important when emerging markets are included.We also show that, in the case of time-varying expected country returns, our adjustment implies a signifficantly smaller variability in portfolio weights than is commonly believed.