Internet Predictions

More than a dozen leading experts give their opinions on where the Internet is headed and where it will be in the next decade in terms of technology, policy, and applications. They cover topics ranging from the Internet of Things to climate change to the digital storage of the future. A summary of the articles is available in the Web extras section

Analogical Predictions

This paper deals with exchangeable analogical predictions,\ud and proposes a Bayesian model for such predictions.\ud The paper first discerns two kinds of analogical\ud predictions, based on similarity of individuals and of types\ud respectively. It then introduces a Bayesian framework that\ud employs hypotheses for making predictions. This framework\ud is used to describe predictions based on the similarity\ud of individuals, and further relates exchangeable predictions\ud with a specific partition of hypotheses on types. Exchangeable\ud predictions based on type similarity are determined by\ud prior probabilities over the partition, but the partition obstructs\ud the control over the similarity relations. Finally the\ud paper develops a model for exchangeable predictions\ud based on type similarity, which employs hypotheses on\ud similarity between individuals, thereby offering a better\ud control over the similarity relations

Unification predictions

The unification of gauge couplings suggests that there is an underlying (supersymmetric) unification of the strong, electromagnetic and weak interactions. The prediction of the unification scale may be the first quantitative indication that this unification may extend to unification with gravity. We make a precise determination of these predictions for a class of models which extend the multiplet structure of the Minimal Supersymmetric Standard Model to include the heavy states expected in many Grand Unified and/or superstring theories. We show that there is a strong cancellation between the 2-loop and threshold effects. As a result the net effect is smaller than previously thought, giving a small increase in both the unification scale and the value of the strong coupling at low energies.Comment: 20 pages, Latex, 5 Postscipt figures; 2 references adde

Higgs-mass predictions

A compilation of Higgs-mass predictions is proposedComment: This is the last version. Only addition: today's update by Kahana & Kahan

Towards String Predictions

The aim of superstring phenomenology is to develop the tools and methodology needed to confront string theory with experimental data. The first mandatory task is to find string solutions which reproduce the observable data. The subsequent goal is to extract potential signatures beyond the observable data. Recently, by studying exact flat directions of non-Abelian singlet fields, we demonstrated the existence of free fermionic heterotic-string models in which the $SU(3)\times SU(2)\times U(1)_Y$-charged matter spectrum, just below the string scale, consists solely of the MSSM spectrum. In this paper we study the possibility that the exact flat directions leave a $U(1)_{Z^\prime}$ symmetry unbroken at the Planck scale. We demonstrate in a specific example that such unbroken $U(1)_{Z^\prime}$ is in general expected to be not of the GUT type but of intrinsic stringy origin. We study its phenomenological characteristics and the consequences in the case that $U(1)_{Z^\prime}$ remains unbroken down to low energies. We suggest that observation in forthcoming colliders of a $Z^\prime$, with universal couplings for the two light generations but different couplings for the heavy generation may provide evidence for the $Z_2\times Z_2$ orbifold which underlies the free fermionic models.Comment: 18 pages. Standard Latex. References adde

Testing earthquake predictions

Statistical tests of earthquake predictions require a null hypothesis to model occasional chance successes. To define and quantify `chance success' is knotty. Some null hypotheses ascribe chance to the Earth: Seismicity is modeled as random. The null distribution of the number of successful predictions -- or any other test statistic -- is taken to be its distribution when the fixed set of predictions is applied to random seismicity. Such tests tacitly assume that the predictions do not depend on the observed seismicity. Conditioning on the predictions in this way sets a low hurdle for statistical significance. Consider this scheme: When an earthquake of magnitude 5.5 or greater occurs anywhere in the world, predict that an earthquake at least as large will occur within 21 days and within an epicentral distance of 50 km. We apply this rule to the Harvard centroid-moment-tensor (CMT) catalog for 2000--2004 to generate a set of predictions. The null hypothesis is that earthquake times are exchangeable conditional on their magnitudes and locations and on the predictions--a common ``nonparametric'' assumption in the literature. We generate random seismicity by permuting the times of events in the CMT catalog. We consider an event successfully predicted only if (i) it is predicted and (ii) there is no larger event within 50 km in the previous 21 days. The $P$-value for the observed success rate is $<0.001$: The method successfully predicts about 5% of earthquakes, far better than `chance,' because the predictor exploits the clustering of earthquakes -- occasional foreshocks -- which the null hypothesis lacks. Rather than condition on the predictions and use a stochastic model for seismicity, it is preferable to treat the observed seismicity as fixed, and to compare the success rate of the predictions to the success rate of simple-minded predictions like those just described. If the proffered predictions do no better than a simple scheme, they have little value.Comment: Published in at http://dx.doi.org/10.1214/193940307000000509 the IMS Collections (http://www.imstat.org/publications/imscollections.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

Primordial Nucleosynthesis: Accurate Predictions

A new accurate evaluation of primordial light nuclei abundances is presented. The proton to neutron conversion rates have been corrected to take into account radiative effects, finite nucleon mass, thermal and plasma corrections. The theoretical uncertainty on 4He is so reduced to the order of 0.1%.Comment: 4 pages, Talk given at the International Workshop on Particles in Astrophysics and Cosmology: From Theory to Observation, Valencia 199

Universality of Bayesian Predictions

Given the sequential update nature of Bayes rule, Bayesian methods find natural application to prediction problems. Advances in computational methods allow to routinely use Bayesian methods in econometrics. Hence, there is a strong case for feasible predictions in a Bayesian framework. This paper studies the theoretical properties of Bayesian predictions and shows that under minimal conditions we can derive finite sample bounds for the loss incurred using Bayesian predictions under the Kullback-Leibler divergence. In particular, the concept of universality of predictions is discussed and universality is established for Bayesian predictions in a variety of settings. These include predictions under almost arbitrary loss functions, model averaging, predictions in a non stationary environment and under model miss-specification. Given the possibility of regime switches and multiple breaks in economic series, as well as the need to choose among different forecasting models, which may inevitably be miss-specified, the finite sample results derived here are of interest to economic and financial forecasting

Assertion, knowledge and predictions

John N. Williams (1994) and Matthew Weiner (2005) invoke predictions in order to undermine the normative relevance of knowledge for assertions; in particular, Weiner argues, predictions are important counterexamples to the Knowledge Account of Assertion (KAA). I argue here that they are not true counterexamples at all, a point that can be agreed upon even by those who reject KAA