Negative association, ordering and convergence of resampling methods

We study convergence and convergence rates for resampling schemes. Our first main result is a general consistency theorem based on the notion of negative association, which is applied to establish the almost-sure weak convergence of measures output from Kitagawa's (1996) stratified resampling method. Carpenter et al's (1999) systematic resampling method is similar in structure but can fail to converge depending on the order of the input samples. We introduce a new resampling algorithm based on a stochastic rounding technique of Srinivasan (2001), which shares some attractive properties of systematic resampling, but which exhibits negative association and therefore converges irrespective of the order of the input samples. We confirm a conjecture made by Kitagawa (1996) that ordering input samples by their states in $\mathbb{R}$ yields a faster rate of convergence; we establish that when particles are ordered using the Hilbert curve in $\mathbb{R}^d$, the variance of the resampling error is ${\scriptscriptstyle\mathcal{O}}(N^{-(1+1/d)})$ under mild conditions, where $N$ is the number of particles. We use these results to establish asymptotic properties of particle algorithms based on resampling schemes that differ from multinomial resampling.Comment: 54 pages, including 30 pages of supplementary materials (a typo in Algorithm 1 has been corrected

Stability with respect to initial conditions in V-norm for nonlinear filters with ergodic observations

AbstractWe establish conditions for an exponential rate of forgetting of the initial distribution of nonlinear filters in V-norm, allowing for unbounded test functions. The analysis is conducted in an general setup involving nonnegative kernels in a random environment which allows treatment of filters and prediction filters in a single framework. The main result is illustrated on two examples, the first showing that a total variation norm stability result obtained by Douc et al. (2009) can be extended to V-norm without any additional assumptions, the second concerning a situation in which forgetting of the initial condition holds in V-norm for the filters, but the V-norm of each prediction filter is infinite.</jats:p

Melodic contour representations in the analysis of children's songs

http://igitur-archive.library.uu.nl/math/2013-0604-200726/UUindex.htmlInternational audienceChildren's songs is a particular musical genre related to folk music, with its own musical characteristics. This paper sets out to explore melodic contour in children's songs from seven different countries/nations across Europe. We look for distinctive contour patterns which differentiate the songs of each country. For pattern representation we use different viewpoints related to melodic contour, two of which also relying on beat information. Preliminary results are presented, and some initial observations regarding the patterns found, the representations used, and the genre as a whole, are discussed

Nudges, social norms and permanence in agri-environmental schemes

The permanence of land management practices adopted under Agri-environmental schemes (AES) is often questioned. This paper investigates the drivers of farmers’ decision as to whether to maintain “pro-environment” practices beyond the duration of a contract, and in particular the effect of social norms. Our results, based on the stated intentions of 395 French farmers, show that both pecuniary and non-pecuniary motivations drive farmers’ decision, which is also significantly influenced by information about a social norm. Therefore “nudging” farmers, by conveying information to them on other farmers’ pro-environmental practices, appears as a means of maintaining the long-run benefits of AES.PostprintPeer reviewe

Terminus-driven retreat of a major southwest Greenland tidewater glacier during the early 19th century : insights from glacier reconstructions and numerical modelling

Peer reviewedPublisher PD

FEATUR.UX: exploiting multitrack information for artistic visualization

FEATUR.UX (Feature - ous) is an audio visualization tool, currently in the process of development, which proposes to introduce a new approach to sound visualization using pre-mixed, independent multitracks and audio feature extraction. Sound visualization is usually performed using a final mix, mono or stereo track of audio. Audio feature extraction is commonly used in the field of music information retrieval to create search and recommendation systems for large music databases rather than generating live visualizations. Visualizing multitrack audio circumvents problems related to the source separation of mixed audio signals and presents an opportunity to examine interdependent relationships within and between separate streams of music. This novel approach to sound visualization aims to provide an enhanced accession to the listening experience corresponding to this use case that employs non-tonal, non-notated forms of electronic music. Findings from prior research studies focused on live performance and preliminary quantitative results from a user survey have provided the basis from which to develop a prototype that will be used throughout an iterative design study to examine the impact of using multitrack audio and audio feature extraction on sound visualization practice

Connected and shared X-in-the-loop technologies for electric vehicle design

The presented paper introduces a new methodology of experimental testing procedures required by the complex systems of electric vehicles (EV). This methodology is based on real-time connection of test setups and platforms, which may be situated in different geographical locations, belong to various cyber-physical domains, and are united in a global X-in-the-loop (XIL) experimental environment. The proposed concept, called XILforEV, allows exploring interdependencies between various physical processes that can be identified or investigated in the process of EV development. The paper discusses the following relevant topics: global XILforEV architecture; realization of required high-confidence models using dynamic data driven application systems (DDDAS) and multi fidelity models (MFM) approaches; and formulation of case studies to illustrate XILforEV application

Short- and long-term effects of a physical activity counselling programme in COPD:A randomized controlled trial

SummaryBackgroundWe were interested in the effects of a physical activity (PA) counselling programme in three groups of COPD patients from general practice (primary care), outpatient clinic (secondary care) and pulmonary rehabilitation (PR).MethodsIn this randomized controlled trial 155 COPD patients, 102 males, median (IQR) age 62 (54–69) y, FEV1predicted 60 (40–75) % were assigned to a 12-weeks' physical activity counselling programme or usual care. Physical activity (pedometer (Yamax SW200) and metabolic equivalents), exercise capacity (6-min walking distance) and quality of life (Chronic Respiratory Questionnaire and Clinical COPD Questionnaire) were assessed at baseline, after three and 15 months.ResultsA significant difference between the counselling and usual care group in daily steps (803 steps, p = 0.001) and daily physical activity (2214 steps + equivalents, p = 0.001)) from 0 to 3 months was found in the total group, as well as in the outpatient (1816 steps, 2616 steps + equivalents, both p = 0.007) and PR (758 steps, 2151 steps + equivalents, both p = 0.03) subgroups. From 0 to 15 months no differences were found in physical activity. However, when patients with baseline physical activity>10,000 steps per day (n = 8), who are already sufficiently active, were excluded, a significant long-term effect of the counselling programme on daily physical activity existed in the total group (p = 0.02). Differences in exercise capacity and quality of life were found only from 0 to 3 months, in the outpatient subgroup.ConclusionOur PA counselling programme effectively enhances PA level in COPD patients after three months. Sedentary patients at baseline still benefit after 15 months.ClinicalTrials.gov: registration number NCT00614796