Multiple imputation for continuous variables using a Bayesian principal component analysis

We propose a multiple imputation method based on principal component analysis (PCA) to deal with incomplete continuous data. To reflect the uncertainty of the parameters from one imputation to the next, we use a Bayesian treatment of the PCA model. Using a simulation study and real data sets, the method is compared to two classical approaches: multiple imputation based on joint modelling and on fully conditional modelling. Contrary to the others, the proposed method can be easily used on data sets where the number of individuals is less than the number of variables and when the variables are highly correlated. In addition, it provides unbiased point estimates of quantities of interest, such as an expectation, a regression coefficient or a correlation coefficient, with a smaller mean squared error. Furthermore, the widths of the confidence intervals built for the quantities of interest are often smaller whilst ensuring a valid coverage.Comment: 16 page

INAUT, a Controlled Language for the French Coast Pilot Books Instructions nautiques

We describe INAUT, a controlled natural language dedicated to collaborative update of a knowledge base on maritime navigation and to automatic generation of coast pilot books (Instructions nautiques) of the French National Hydrographic and Oceanographic Service SHOM. INAUT is based on French language and abundantly uses georeferenced entities. After describing the structure of the overall system, giving details on the language and on its generation, and discussing the three major applications of INAUT (document production, interaction with ENCs and collaborative updates of the knowledge base), we conclude with future extensions and open problems.Comment: 10 pages, 3 figures, accepted for publication at Fourth Workshop on Controlled Natural Language (CNL 2014), 20-22 August 2014, Galway, Irelan

Citizens’ behaviours related to smoke in bushfires and their implications for computational models of evacuation

The behaviours of citizens during bushfires may determine whether they live or die. Using 100 citizen witness statements from the 2009 Australian bushfires, we show how people react to bushfire smoke. Eighty-nine witnesses expressly mention smoke, not necessarily in combination with fire. This prompted behaviours including: seeking further information, monitoring the situation, effecting a fire plan (including evacuation), alerting people to danger and fire risk, and going home. Computational simulators have been used to assess civilians’ risk and to help with evacuation efforts. Despite works that accurately model fire spread and people’s behaviours in response to perceiving fire, the issue of how people react to seeing smoke from a bushfire is rarely considered. We discuss how the identified behaviours may be incorporated into an agent-based simulator of bushfire

Downscaling long term socio-economic scenarios at city scale: A case study on Paris

International audienceThe NEDUM-2D model is used to downscale four global socioeconomic scenarios at city scale and simulate the evolution of the Paris urban area between 1900 and 2100. It is based on a dynamic extension of the classical urban economic theory, to explain the spatial distribution of land and real estate values, dwelling surfaces, population density and buildings heights and density. A validation over the 1900-2010 period shows that the model reproduces available data and captures the main determinants of city shape evolution. From four global scenarios and additional local inputs, 32 local scenarios are created and analyzed. Main drivers of urban sprawl and climate and flood vulnerability appear to be local demographic growth and local policies; global factors, such as energy and transport prices, even including possible peak-oil and carbon taxes, have only a limited influence on them. Conversely, transport-related greenhouse gases emissions are mainly driven by global factors, namely vehicle efficiency changes, not by land use. As a consequence, very strict urban policies — including reconstruction — would become necessary to control emissions from urban transportation if technologies reveal unable to do so. These scenarios are a useful input for the design and assessment of mitigation and adaptation policies at local scale

Imputation de données manquantes pour des données mixtes via les méthodes factorielles grâce à missMDA

Imputation de données manquantes pour des données mixtes via les méthodes factorielles grâce à missMD