On improving the forecast accuracy of the hidden Markov model

The forecast accuracy of a hidden Markov model (HMM) may be low due first, to the measure of forecast accuracy being ignored in the parameterestimation method and, second, to overfitting caused by the large number of parameters that must be estimated. A general approach to forecasting is described which aims to resolve these two problems and so improve the forecast accuracy of the HMM. First, the application of extremum estimators to the HMM is proposed. Extremum estimators aim to improve the forecast accuracy of the HMM by minimising an estimate of the forecast error on the observed data. The forecast accuracy is measured by a score function and the use of some general classes of score functions is proposed. This approach contrasts with the standard use of a minus log-likelihood score function. Second, penalised estimation for the HMM is described. The aim of penalised estimation is to reduce overfitting and so increase the forecast accuracy of the HMM. Penalties on both the state-dependent distribution parameters and transition probability matrix are proposed. In addition, a number of cross-validation approaches for tuning the penalty function are investigated. Empirical assessment of the proposed approach on both simulated and real data demonstrated that, in terms of forecast accuracy, penalised HMMs fitted using extremum estimators generally outperformed unpenalised HMMs fitted using maximum likelihood

Persistent current formation in a high-temperature Bose-Einstein condensate: an experimental test for c-field theory

Experimental stirring of a toroidally trapped Bose-Einstein condensate at high temperature generates a disordered array of quantum vortices that decays via thermal dissipation to form a macroscopic persistent current [T. W. Neely em et al. arXiv:1204.1102 (2012)]. We perform 3D numerical simulations of the experimental sequence within the Stochastic Projected Gross-Pitaevskii equation using ab initio determined reservoir parameters. We find that both damping and noise are essential for describing the dynamics of the high-temperature Bose field. The theory gives a quantitative account of the formation of a persistent current, with no fitted parameters.Comment: v2: 7 pages, 3 figures, new experimental data and numerical simulation

Does benchmarking of rating scales improve ratings of search performance given by specialist search dog handlers?

Rating scales are widely used to rate working dog behavior and performance. Whilst behaviour scales have been extensively validated, instruments used to rate ability have usually been designed by training and practitioner organizations, and often little consideration has been given to how seemingly insignificant aspects of the scale design might alter the validity of the results obtained. Here we illustrate how manipulating one aspect of rating scale design, the provision of verbal benchmarks or labels (as opposed to just a numerical scale), can affect the ability of observers to distinguish between differing levels of search dog performance in an operational environment. Previous studies have found evidence for range restriction (using only part of the scale) in raters' use of the scales and variability between raters in their understanding of the traits used to measures performance. As provision of verbal benchmarks has been shown to help raters in a variety of disciplines to select appropriate scale categories (or scores), it may be predicted that inclusion of verbal benchmarks will bring raters' conceptualization of the traits closer together, increasing agreement between raters, as well as improving the ability of observers to distinguish between differing levels of search dog performance and reduce range restriction. To test the value of verbal benchmarking we compared inter-rater reliability, raters' ability to discriminate between different levels of search dog performance, and their use of the whole scale before and after being presented with benchmarked scales for the same traits. Raters scored the performance of two separate types of explosives search dog (High Assurance Search (HAS) and Vehicle Search (VS) dogs), from short (~30 s) video clips, using 11 previously validated traits. Taking each trait in turn, for the first five clips raters were asked to give a score from 1, representing the lowest amount of the trait evident to 5, representing the highest. Raters were given a list of adjective-based benchmarks (e.g., very low, low, intermediate, high, very high) and scored a further five clips for each trait. For certain traits, the reliability of scoring improved when benchmarks were provided (e.g., Motivation and Independence), indicating that their inclusion may potentially reduce ambivalence in scoring, ambiguity of meanings, and cognitive difficulty for raters. However, this effect was not universal, with the ratings of some traits remaining unchanged (e.g., Control), or even reducing in reliability (e.g., Distraction). There were also some differences between VS and HAS (e.g., Confidence reliability increased for VS raters and decreased for HAS raters). There were few improvements in the spread of scores across the range, but some indication of more favorable scoring. This was a small study of operational handlers and trainers utilizing training video footage from realistic operational environments, and there are potential cofounding effects. We discuss possible causal factors, including issues specific to raters and possible deficiencies in the chosen benchmarks, and suggest ways to further improve the effectiveness of rating scales. This study illustrates why it is vitally important to validate all aspects of rating scale design, even if they may seem inconsequential, as relatively small changes to the amount and type of information provided to raters can have both positive and negative impacts on the data obtained

Suppression of Kelvon-induced decay of quantized vortices in oblate Bose-Einstein Condensates

We study the Kelvin mode excitations on a vortex line in a three-dimensional trapped Bose-Einstein condensate at finite temperature. Our stochastic Gross-Pitaevskii simulations show that the activation of these modes can be suppressed by tightening the confinement along the direction of the vortex line, leading to a strong suppression in the vortex decay rate as the system enters a regime of two-dimensional vortex dynamics. As the system approaches the condensation transition temperature we find that the vortex decay rate is strongly sensitive to dimensionality and temperature, observing a large enhancement for quasi-two-dimensional traps. Three-dimensional simulations of the recent vortex dipole decay experiment of Neely et al. [Phys. Rev. Lett. 104, 160401 (2010)] confirm two-dimensional vortex dynamics, and predict a dipole lifetime consistent with experimental observations and suppression of Kelvon-induced vortex decay in highly oblate condensates.Comment: 8 pages, 8 figure