Bayesian Learning for a Class of Priors with Prescribed Marginals

We present Bayesian updating of an imprecise probability measure, represented by a class of precise multidimensional probability measures. Choice and analysis of our class are motivated by expert interviews that we conducted with modelers in the context of climatic change. From the interviews we deduce that generically, experts hold a much more informed opinion on the marginals of uncertain parameters rather than on their correlations. Accordingly, we specify the class by prescribing precise measures for the marginals while letting the correlation structure subject to complete ignorance. For sake of transparency, our discussion focuses on the tutorial example of a linear two-dimensional Gaussian model. We operationalize Bayesian learning for that class by various updating rules, starting with (a modified version of) the generalized Bayes' rule and the maximum likelihood update rule (after Gilboa and Schmeidler). Over a large range of potential observations, the generalized Bayes' rule would provide non-informative results. We restrict this counter-intuitive and unnecessary growth of uncertainty by two means, the discussion of which refers to any kind of imprecise model, not only to our class. First, we find our class of priors too inclusive and, hence, require certain additional properties of prior measures in terms of smoothness of probability density functions. Second, we argue that both updating rules are dissatisfying, the generalized Bayes' rule being too conservative, i.e., too inclusive, the maximum likelihood rule being too exclusive. Instead, we introduce two new ways of Bayesian updating of imprecise probabilities: a ``weighted maximum likelihood method'' and a ``semi-classical method.'' The former bases Bayesian updating on the whole set of priors, however, with weighted influence of its members. By referring to the whole set, the weighted maximum likelihood method allows for more robust inferences than the standard maximum likelihood method and, hence, is better to justify than the latter.Furthermore, the semi-classical method is more objective than the weighted maximum likelihood method as it does not require the subjective definition of a weighting function. Both new methods reveal much more informative results than the generalized Bayes' rule, what we demonstrate for the example of a stylized insurance model

Industrial design at General Motors

http://deepblue.lib.umich.edu/bitstream/2027.42/96908/1/BBA_Held_Thomas_Winter_1998_final.pd

Feed-in Tariffs and Quotas for Renewable Energy in Europe

Regenerative Energie, Elektrizität, Stromtarif, Förderung regenerativer Energien, EU-Staaten, Renewable energy, Electricity, Electricity price, Renewable energy policy, EU countries

A SUSTAINABLE HERBICIDE AND GRASS ESTABLISHMENT APPROACH FOR LAND RECLAMATION: A CASE OF RUSSIAN KNAPWEED

Controlling Russian knapweed with an integrated system of herbicide followed by seeding perennial grass is profitable in yielding an 8.7% average rate of return, and repaying the establishment costs in approximately six years. Moreover, the system is sustainable by exploiting plant competition and eliminating herbicide usage in later years.Land Economics/Use,

Bank Culture and the Official Sector: A Spectrum of Options

If you think culture is too squishy, please hear us out. In Part I of this Article, we set out what we mean by culture. In Part II, we explain why we are interested in culture and why it matters to us now. In Part III, we will survey the work of other public authorities in their efforts to address culture. In our view, these efforts fall into several categories along a spectrum from more advisory to more prescriptive. We do not endorse any particular method. All of these efforts are useful attempts to address a common problem: repeated ethical failures that undermine the trustworthiness of financial services. We hope this Part will direct interested academics to useful source material and demonstrate the value of the various different approaches. In Part IV, we will focus on what the Federal Reserve Bank of New York (the New York Fed) has done to address culture. These efforts fall on the advisory end of the spectrum of available tools covered in Part III. This reflects, in part, the New York Fed’s role within the Federal Reserve, the central bank of the United States. Finally, in Part V, we pose a few questions for further discussion in academic forums: 1. What are we missing about culture? 2. What else should we and our colleagues at the Federal Reserve Bank of New York do? 3. How do we know if there has been progress? This Article does not include the customary survey of scholarly literature; we leave that to the more academically focused. Our purpose is not to fill gaps in what theorists and researchers have written. In addition, we avoid stating how financial institutions have approached culture, except where their efforts are public or described by other public authorities. This approach avoids concerns about inadvertently disclosing any confidential supervisory information

Quantitative multichannel NC-AFM data analysis of graphene growth on SiC(0001)

Noncontact atomic force microscopy provides access to several complementary signals, such as topography, damping, and contact potential. The traditional presentation of such data sets in adjacent figures or in colour-coded pseudo-three-dimensional plots gives only a qualitative impression. We introduce two-dimensional histograms for the representation of multichannel NC-AFM data sets in a quantitative fashion. Presentation and analysis are exemplified for topography and contact-potential data for graphene grown epitaxially on 6H-SiC(0001), as recorded by Kelvin probe force microscopy in ultrahigh vacuum. Sample preparations by thermal decomposition in ultrahigh vacuum and in an argon atmosphere are compared and the respective growth mechanisms discussed