10,335 research outputs found

    Statistical estimation of a growth-fragmentation model observed on a genealogical tree

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    We model the growth of a cell population by a piecewise deterministic Markov branching tree. Each cell splits into two offsprings at a division rate B(x)B(x) that depends on its size xx. The size of each cell grows exponentially in time, at a rate that varies for each individual. We show that the mean empirical measure of the model satisfies a growth-fragmentation type equation if structured in both size and growth rate as state variables. We construct a nonparametric estimator of the division rate B(x)B(x) based on the observation of the population over different sampling schemes of size nn on the genealogical tree. Our estimator nearly achieves the rate n−s/(2s+1)n^{-s/(2s+1)} in squared-loss error asymptotically. When the growth rate is assumed to be identical for every cell, we retrieve the classical growth-fragmentation model and our estimator improves on the rate n−s/(2s+3)n^{-s/(2s+3)} obtained in \cite{DHRR, DPZ} through indirect observation schemes. Our method is consistently tested numerically and implemented on {\it Escherichia coli} data.Comment: 46 pages, 4 figure

    Cooperation, the power of a single word. Some experimental evidence on wording and gender effects in a Game of Chicken

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    Wording has been widely shown to affect decision making. In this paper, we investigate experimentally whether and to what extent, cooperative behaviour in a Game of Chicken may be impated by a very basic change in the labelling of the strategies. Our within-subject experimental design involves two treatments. The only difference between them is that we introduce either a socially-oriented wording (‘I cooperate'/‘I do not cooperate') or colours (red/blue) to designate strategies. The level of cooperation appears to be higher in the socially-oriented context, but only when the uncertainty as regards the type of the partner is manipulated, and especially among females.Social dilemma, Game of Chicken, cooperation, wording effects, gender effects.

    Paris Declaration Country Evaluations: How Solid is the Evidence? META-Evaluation of the Country Evaluations of the Phase II Paris Declaration Evaluation

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    The evaluation of the Paris Declaration (PD) is one of the most important and challenging evaluative undertakings of the past decade in the aid sector. The PD evaluation commissioned by the OECD/DAC Evaluation Network consists of a set of independent crosscountry and donor evaluations which were carried out in two phases. The scope and importance of this evaluation makes it a particularly suitable subject for a meta-evaluation. Our 'evaluation of the evaluation’ complements the official meta-evaluation of the synthesis report in that it assesses all country evaluation reports available in English (15 out of 21 reports) using the OECD/DAC Evaluation Quality Standards. Two research questions are central in our undertaking: Is the quality of the country evaluation reports good enough to be included in the synthesis report? Do the reports properly comply with the evaluation framework to permit comparison of evaluation across countries? The findings of the meta-evaluation demonstrate that comparability of country evaluation reports is satisfactory. The quality of evidence, however, is questionable, due to various limitations and constraints that plagued several country evaluations. Therefore, the inclusion of some of the country reports in the evaluation synthesis report is questionable.

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    Cat in the Throat: Caroline Bergvall's plurilingual bodies

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    Scholarships & Prizes Office. University of Sydne

    Neural Networks for Complex Data

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    Artificial neural networks are simple and efficient machine learning tools. Defined originally in the traditional setting of simple vector data, neural network models have evolved to address more and more difficulties of complex real world problems, ranging from time evolving data to sophisticated data structures such as graphs and functions. This paper summarizes advances on those themes from the last decade, with a focus on results obtained by members of the SAMM team of Universit\'e Paris
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