arXiv: Applications最新文献_第10页

A stochastic space-time model for intermittent precipitation occurrences 间歇性降水发生的随机时空模型

arXiv: Applications Pub Date : 2016-02-09 DOI: 10.1214/15-AOAS875

Ying Sun, M. Stein

引用次数: 24

Modeling competition between two pharmaceutical drugs using innovation diffusion models 利用创新扩散模型对两种药物之间的竞争进行建模

arXiv: Applications Pub Date : 2016-02-09 DOI: 10.1214/15-AOAS868

R. Guseo, C. Mortarino

引用次数: 26

The discriminative functional mixture model for a comparative analysis of bike sharing systems 基于判别函数混合模型的共享单车系统对比分析

arXiv: Applications Pub Date : 2016-01-29 DOI: 10.1214/15-AOAS861

C. Bouveyron, E. Côme, J. Jacques

{"title":"The discriminative functional mixture model for a comparative analysis of bike sharing systems","authors":"C. Bouveyron, E. Côme, J. Jacques","doi":"10.1214/15-AOAS861","DOIUrl":"https://doi.org/10.1214/15-AOAS861","url":null,"abstract":"Bike sharing systems (BSSs) have become a means of sustainable intermodal transport and are now proposed in many cities worldwide. Most BSSs also provide open access to their data, particularly to real-time status reports on their bike stations. The analysis of the mass of data generated by such systems is of particular interest to BSS providers to update system structures and policies. This work was motivated by interest in analyzing and comparing several European BSSs to identify common operating patterns in BSSs and to propose practical solutions to avoid potential issues. Our approach relies on the identification of common patterns between and within systems. To this end, a model-based clustering method, called FunFEM, for time series (or more generally functional data) is developed. It is based on a functional mixture model that allows the clustering of the data in a discriminative functional subspace. This model presents the advantage in this context to be parsimonious and to allow the visualization of the clustered systems. Numerical experiments confirm the good behavior of FunFEM, particularly compared to state-of-the-art methods. The application of FunFEM to BSS data from JCDecaux and the Transport for London Initiative allows us to identify 10 general patterns, including pathological ones, and to propose practical improvement strategies based on the system comparison. The visualization of the clustered data within the discriminative subspace turns out to be particularly informative regarding the system efficiency. The proposed methodology is implemented in a package for the R software, named funFEM, which is available on the CRAN. The package also provides a subset of the data analyzed in this work.","PeriodicalId":409996,"journal":{"name":"arXiv: Applications","volume":"273 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116847814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 108

Assessing differences in legislators' revealed preferences: A case study on the 107th U.S. Senate 评估立法者透露的偏好差异:对第107届美国参议院的案例研究

arXiv: Applications Pub Date : 2016-01-28 DOI: 10.1214/16-AOAS951

Chelsea Lofland, Abel Rodríguez, Scott Moser

引用次数: 6

Lateral transfer in Stochastic Dollo models 随机Dollo模型中的横向转移

arXiv: Applications Pub Date : 2016-01-28 DOI: 10.1214/17-AOAS1040

Luke J Kelly, G. Nicholls

引用次数: 10

Automatic Matching of Bullet Land Impressions 自动匹配子弹地面印痕

arXiv: Applications Pub Date : 2016-01-21 DOI: 10.1214/17-AOAS1080

E. Hare, H. Hofmann, A. Carriquiry

引用次数: 30

Trajectory clustering, modelling, and selection with the focus on airspace protection 以空域保护为重点的轨迹聚类、建模和选择

arXiv: Applications Pub Date : 2016-01-14 DOI: 10.2514/6.2016-1411

W. Eerland, S. Box

{"title":"Trajectory clustering, modelling, and selection with the focus on airspace protection","authors":"W. Eerland, S. Box","doi":"10.2514/6.2016-1411","DOIUrl":"https://doi.org/10.2514/6.2016-1411","url":null,"abstract":"Take-off and landing are the periods of a flight where aircraft are most vulnerable to a ground based rocket attack by terrorists. While aircraft approach and depart from airports on pre-defined flight paths, there is a degree of uncertainty in the trajectory of each individual aircraft. Capturing and characterizing these deviations is important for accurate strategic planning for the defence of airports against terrorist attack. A methodology is demonstrated whereby approach and departure trajectories to a given airport are characterized statistically from historical data. It uses a two-step process of first clustering to extract the common trend, and then modelling uncertainty using Gaussian processes. Furthermore it is shown that this approach can be used to either select probabilistic regions of airspace where trajectories are likely and - if required - can automatically generate a set of representative trajectories, or select key trajectories that are both likely and critically vulnerable. An evaluation of the methodology is demonstrated on an example data-set collected by the ground radar at an airport. The evaluation indicates that 99.8% of the calculated footprint underestimates less than 5% when replacing the original trajectory data with a set of representative trajectories","PeriodicalId":409996,"journal":{"name":"arXiv: Applications","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132251705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 20

Smooth Principal Component Analysis over two-dimensional manifolds with an application to Neuroimaging 二维流形的平滑主成分分析及其在神经成像中的应用

arXiv: Applications Pub Date : 2016-01-05 DOI: 10.1214/16-AOAS975

E. Lila, J. Aston, L. Sangalli

引用次数: 57

Estimating changes in temperature extremes from millennial scale climate simulations using generalized extreme value (GEV) distributions 利用广义极值(GEV)分布估算千年尺度气候模拟的极端温度变化

arXiv: Applications Pub Date : 2015-12-29 DOI: 10.5194/ASCMO-2-79-2016

Whitney K. Huang, M. Stein, D. McInerney, Shanshan Sun, E. Moyer

{"title":"Estimating changes in temperature extremes from millennial scale climate simulations using generalized extreme value (GEV) distributions","authors":"Whitney K. Huang, M. Stein, D. McInerney, Shanshan Sun, E. Moyer","doi":"10.5194/ASCMO-2-79-2016","DOIUrl":"https://doi.org/10.5194/ASCMO-2-79-2016","url":null,"abstract":"Changes in extreme weather may produce some of the largest societal impacts of anthropogenic climate change. However, it is intrinsically difficult to estimate changes in extreme events from the short observational record. In this work we use millennial runs from the CCSM3 in equilibrated pre-industrial and possible future conditions to examine both how extremes change in this model and how well these changes can be estimated as a function of run length. We estimate changes to distributions of future temperature extremes (annual minima and annual maxima) in the contiguous United States by fitting generalized extreme value (GEV) distributions. Using 1000-year pre-industrial and future time series, we show that the magnitude of warm extremes largely shifts in accordance with mean shifts in summertime temperatures. In contrast, cold extremes warm more than mean shifts in wintertime temperatures, but changes in GEV location parameters are largely explainable by mean shifts combined with reduced wintertime temperature variability. In addition, changes in the spread and shape of the GEV distributions of cold extremes at inland locations can lead to discernible changes in tail behavior. We then examine uncertainties that result from using shorter model runs. In principle, the GEV distribution provides theoretical justification to predict infrequent events using time series shorter than the recurrence frequency of those events. To investigate how well this approach works in practice, we estimate 20-, 50-, and 100-year extreme events using segments of varying lengths. We find that even using GEV distributions, time series that are of comparable or shorter length than the return period of interest can lead to very poor estimates. These results suggest caution when attempting to use short observational time series or model runs to infer infrequent extremes.","PeriodicalId":409996,"journal":{"name":"arXiv: Applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125357946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 55

Estimation of Kullback-Leibler losses for noisy recovery problems within the exponential family 指数族内噪声恢复问题的Kullback-Leibler损失估计

arXiv: Applications Pub Date : 2015-12-27 DOI: 10.1214/17-EJS1321

C. Deledalle

引用次数: 11