An exploratory canonical analysis approach for multinomial populations based on the ϕ\phi-divergence measure

summary:In this paper we consider an exploratory canonical analysis approach for multinomial population based on the $\phi$-divergence measure. We define the restricted minimum $\phi$-divergence estimator, which is seen to be a generalization of the restricted maximum likelihood estimator. This estimator is then used in $\phi$-divergence goodness-of-fit statistics which is the basis of two new families of statistics for solving the problem of selecting the number of significant correlations as well as the appropriateness of the model

A Wiener--Hopf Monte Carlo simulation technique for L\'{e}vy processes

We develop a completely new and straightforward method for simulating the joint law of the position and running maximum at a fixed time of a general L\'{e}vy process with a view to application in insurance and financial mathematics. Although different, our method takes lessons from Carr's so-called "Canadization" technique as well as Doney's method of stochastic bounds for L\'{e}vy processes; see Carr [Rev. Fin. Studies 11 (1998) 597--626] and Doney [Ann. Probab. 32 (2004) 1545-1552]. We rely fundamentally on the Wiener-Hopf decomposition for L\'{e}vy processes as well as taking advantage of recent developments in factorization techniques of the latter theory due to Vigon [Simplifiez vos L\'{e}vy en titillant la factorization de Wiener-Hopf (2002) Laboratoire de Math\'{e}matiques de L'INSA de Rouen] and Kuznetsov [Ann. Appl. Probab. 20 (2010) 1801--1830]. We illustrate our Wiener--Hopf Monte Carlo method on a number of different processes, including a new family of L\'{e}vy processes called hypergeometric L\'{e}vy processes. Moreover, we illustrate the robustness of working with a Wiener--Hopf decomposition with two extensions. The first extension shows that if one can successfully simulate for a given L\'{e}vy processes then one can successfully simulate for any independent sum of the latter process and a compound Poisson process. The second extension illustrates how one may produce a straightforward approximation for simulating the two-sided exit problem.Comment: Published in at http://dx.doi.org/10.1214/10-AAP746 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

Engagement-related process factors in services for street-connected children and young people in low and middle income countries: a thematic synthesis

A recent Cochrane/ Campbell systematic review of interventions for promoting reintegration and reducing harmful behaviour and lifestyles in street-connected children and young people, supported by the International Initiative for Impact Evaluation (3ie), identified 11 studies evaluating 12 different interventions which met the inclusion criteria (Coren et al. 2013). The research studies had to contain a comparison group and look at street-connected children and young people between the ages of 0 and 24. None of the included studies were from low- and middle-income countries (LMICs), or involved process evaluations. The current thematic synthesis focused on engagement processes and strategies in studies pertaining to LMICs but excluded from the review on methodological grounds, complemented by studies identified through a search update conducted in March 2013. We included twenty-seven qualitative or mixed methods studies, which examined broad range of interventions and services adopted in 21 LMICs. The synthesis methods were primarily qualitative. On the basis of our findings, we conceptualised engagement as consisting of outreach and sustaining phases. Three separate dimensions emerged in the sustaining phases: meeting multiple needs, relations to adult service users, and community and family engagement. Our synthesis outlines challenges and dilemmas of engagement in each of these areas. The data also highlighted some common shortcomings in the service sector in LMICs, including lack of appropriate professional training and service development, lack of funding, and lack of co-operation with other relevant agencies. Innovative approaches to engagement, such as participatory initiatives and partnerships with universities, are also discussed

Multiple Charge State Beam Acceleration at Atlas

A test of the acceleration of multiple charge-state uranium beams was performed at the ATLAS accelerator. A 238U+26 beam was accelerated in the ATLAS PII linac to 286 MeV (~1.2 MeV/u) and stripped in a carbon foil located 0.5 m from the entrance of the ATLAS Booster section. A 58Ni9+ 'guide' beam from the tandem injector was used to tune the Booster for 238U+38. All charge states from the stripping were injected into the booster and accelerated. Up to 94% of the beam was accelerated through the Booster linac, with losses mostly in the lower charge states. The measured beam properties of each charge state and a comparison to numerical simulations are reported in this paper.Comment: LINAC2000, MOD0

Conditional tests of marginal homogeneity based on ϕ-divergence test statistics

AbstractIn this work, using the well-known result that symmetry is equivalent to quasi-symmetry and marginal homogeneity simultaneously holding, two families of test statistics based on ϕ-divergence measures are introduced for testing conditional marginal homogeneity assuming that quasi-symmetry holds

Exploiting Evolution for an Adaptive Drift-Robust Classifier in Chemical Sensing

Gas chemical sensors are strongly affected by drift, i.e., changes in sensors' response with time, that may turn statistical models commonly used for classification completely useless after a period of time. This paper presents a new classifier that embeds an adaptive stage able to reduce drift effects. The proposed system exploits a state-of-the-art evolutionary strategy to iteratively tweak the coefficients of a linear transformation able to transparently transform raw measures in order to mitigate the negative effects of the drift. The system operates continuously. The optimal correction strategy is learnt without a-priori models or other hypothesis on the behavior of physical-chemical sensors. Experimental results demonstrate the efficacy of the approach on a real problem