Chi-square and Poissonian Data: Biases Even in the High-Count Regime and How to Avoid them

We demonstrate that two approximations to the chi^2 statistic as popularly employed by observational astronomers for fitting Poisson-distributed data can give rise to intrinsically biased model parameter estimates, even in the high counts regime, unless care is taken over the parameterization of the problem. For a small number of problems, previous studies have shown that the fractional bias introduced by these approximations is often small when the counts are high. However, we show that for a broad class of problem, unless the number of data bins is far smaller than \sqrt{N_c}, where N_c is the total number of counts in the dataset, the bias will still likely be comparable to, or even exceed, the statistical error. Conversely, we find that fits using Cash's C-statistic give comparatively unbiased parameter estimates when the counts are high. Taking into account their well-known problems in the low count regime, we conclude that these approximate chi^2 methods should not routinely be used for fitting an arbitrary, parameterized model to Poisson-distributed data, irrespective of the number of counts per bin, and instead the C-statistic should be adopted. We discuss several practical aspects of using the C-statistic in modelling real data. We illustrate the bias for two specific problems, measuring the count-rate from a lightcurve and obtaining the temperature of a thermal plasma from its X-ray spectrum measured with the Chandra X-ray observatory. In the context of X-ray astronomy, we argue the bias could give rise to systematically mis-calibrated satellites and a ~5-10% shift in galaxy cluster scaling relations.Comment: 9 pages, 2 figures. Accepted for publication in the Astrophysical Journa

Electronic commerce An open electronic marketplace through agent-based workflows: MOPPET

Abstract. We propose an electronic marketplace architecture, called MOPPET, where the commerce processes in the marketplace are modeled as adaptable agent-based workflows. The higher level of abstraction provided by the workflow technology makes the customization of electronic commerce processes for different users possible. Agent-based implementation, on the other hand, provides for a highly reusable component-based workflow architecture as well as negotiation ability and the capability to adapt to dynamic changes in the environment. Agent communication is handled through Knowledge Query and Manipulation Language (KQML). A workflow-based architecture also makes it possible for complete modeling of electronic commerce processes by allowing involved parties to be able to invoke already existing applications or to define new tasks and to re-structure the control and data flow among the tasks to create custom built process definitions. In the proposed architecture all data exchanges are realized through Extensible Markup Language (XML) providing uniformity, simplicity and a highly open and interoperable architecture. Metadata of activities are expressed through Resource Description Framework (RDF). Common Business Library (CBL) is used for achieving interoperability across business domains and domain specific Document Type Definitions (DTDs) are used for vertical industries. We provide our own specifications for missing DTDs to be replaced by the original specifications when they become available

ISURF: RFID Enabled Collaborative Supply Chain Planning Environment

To be able to cope with the requirements of today’s competitive and demanding digital world of business, companies, especially SMEs, need to be more agile, and be ready to react to the changing requirements of the sector. This requires a better view and a more comprehensive analysis of the whole marketplace which can be achieved through a knowledge oriented collaborative supply chain planning initiative. The parties also need to be capable of monitoring the supply chain visibility in a real time fashion, which can be enabled through the use of RFID devices. RFID enabled collaborative supply chain planning has been achieved by big industry players in well defined restricted business circumstances through some selected standard message schemes. However, SMEs are still far behind in this process due to their small IT budgets. In iSURF Project we address this problem by providing a set of open source tools to enable seamless collection of supply chain visibility, synchronizing this with master data, exchanging supply chain visibility and other planning data with each other through a service oriented supply chain planning environment which also handles the interoperability of the messages exchanged

iCARDEA: Practical Data Integration for the Follow-up of Cardiovascular Implantable Electronic Device Patients in Cardiology Departments

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Electronic Document Interoperability in eBusiness and eGovernment Applications

Businesses and Government Organizations need to exchange documents to execute transactions with the parties they trade or collaborate with [...