The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform

Luciana Aguiar Figueredo - One of the best experts on this subject based on the ideXlab platform.

  • SSDBM - A user-friendly interface for mainframe
    Seventh International Working Conference on Scientific and Statistical Database Management, 1994
    Co-Authors: M.s.s. Cabral, Luciana Aguiar Figueredo
    Abstract:

    SIDRA II System was developed to provide on-line access to aggregate data resulted from all censuses and surveys produced by IBGE, as National Statistical System Coordinator in Brazil. The main goal was to have a user-friendly interface and provide dense information (data and metadata), as well as facilities for data retrieval based on a mainframe environment. >

Matthew D. Shapiro - One of the best experts on this subject based on the ideXlab platform.

  • Effects of a Government-Academic Partnership: Has the NSF-CENSUS Bureau Research Network Helped Improve the US Statistical System?
    Journal of Survey Statistics and Methodology, 2018
    Co-Authors: Daniel H. Weinberg, John M. Abowd, Robert F. Belli, Noel A Cressie, David C. Folch, Scott H. Holan, Margaret C. Levenstein, Kristen M. Olson, Jerome P. Reiter, Matthew D. Shapiro
    Abstract:

    This paper began as a May 8, 2015 presentation to the National Academies of Science’s Committee on National Statistics by two of the principal investigators of the National Science Foundation-Census Bureau Research Network (NCRN) – John Abowd and the late Steve Fienberg (Carnegie Mellon University). The authors acknowledge the contributions of the other principal investigators of the NCRN who are not co-authors of the paper (William Block, William Eddy, Alan Karr, Charles Manski, Nicholas Nagle, and Rebecca Nugent), the co- principal investigators, and the comments of Patrick Cantwell, Constance Citro, Adam Eck, Brian Harris-Kojetin, and Eloise Parker. We note with sorrow the deaths of Stephen Fienberg and Allan McCutcheon, two of the original NCRN principal investigators. The principal investigators also wish to acknowledge Cheryl Eavey’s sterling grant administration on behalf of the NSF. The conclusions reached in this paper are not the responsibility of the National Science Foundation (NSF), the Census Bureau, or any of the institutions to which the authors belong

  • Effects of a Government-Academic Partnership: Has the NSF-Census Bureau Research Network Helped Secure the Future of the Federal Statistical System?
    2017
    Co-Authors: Daniel H. Weinberg, John M. Abowd, Robert F. Belli, Noel A Cressie, David C. Folch, Scott H. Holan, Margaret C. Levenstein, Jerome P. Reiter, Kristen Olson, Matthew D. Shapiro
    Abstract:

    This paper began as a May 8, 2015 presentation to the National Academies of Science’s Committee on National Statistics by two of the principal investigators of the National Science Foundation-Census Bureau Research Network (NCRN) – John Abowd and the late Steve Fienberg (Carnegie Mellon University). The authors acknowledge the contributions of the other principal investigators of the NCRN who are not co-authors of the paper (William Block, William Eddy, Alan Karr, Charles Manski, Nicholas Nagle, and Rebecca Nugent), the co- principal investigators, and the comments of Patrick Cantwell, Constance Citro, Adam Eck, Brian Harris-Kojetin, and Eloise Parker. We note with sorrow the deaths of Stephen Fienberg and Allan McCutcheon, two of the original NCRN principal investigators. The principal investigators also wish to acknowledge Cheryl Eavey’s sterling grant administration on behalf of the NSF. The conclusions reached in this paper are not the responsibility of the National Science Foundation (NSF), the Census Bureau, or any of the institutions to which the authors belong

  • Effects of a Government-Academic Partnership: Has the NSF-Census Bureau Research Network Helped Improve the U.S. Statistical System?
    2017
    Co-Authors: Daniel H. Weinberg, John M. Abowd, Robert F. Belli, Noel A Cressie, David C. Folch, Scott H. Holan, Margaret C. Levenstein, Jerome P. Reiter, Kristen Olson, Matthew D. Shapiro
    Abstract:

    The National Science Foundation-Census Bureau Research Network (NCRN) was established in 2011 to create interdisciplinary research nodes on methodological questions of interest and significance to the broader research community and to the Federal Statistical System (FSS), particularly the Census Bureau. The activities to date have covered both fundamental and applied Statistical research and have focused at least in part on the training of current and future generations of researchers in skills of relevance to surveys and alternative measurement of economic units, households, and persons. This paper discusses some of the key research findings of the eight nodes, organized into six topics: (1) Improving census and survey data collection methods; (2) Using alternative sources of data; (3) Protecting privacy and confidentiality by improving disclosure avoidance; (4) Using spatial and spatio-temporal Statistical modeling to improve estimates; (5) Assessing data cost and quality tradeoffs; and (6) Combining information from multiple sources. It also reports on collaborations across nodes and with federal agencies, new software developed, and educational activities and outcomes. The paper concludes with an evaluation of the ability of the FSS to apply the NCRN’s research outcomes and suggests some next steps, as well as the implications of this research-network model for future federal government renewal initiatives.

Dmitry Ignatyev - One of the best experts on this subject based on the ideXlab platform.

  • Cosmological evolution of Statistical System of scalar charged particles
    Astrophysics and Space Science, 2015
    Co-Authors: Yurii Ignat'ev, Alexander Agathonov, Mikhail Mikhailov, Dmitry Ignatyev
    Abstract:

    In the paper we consider the macroscopic model of plasma of scalar charged particles, obtained by means of the Statistical averaging of the microscopic equations of particle dynamics in a scalar field. On the basis of kinetic equations, obtained from averaging, and their strict integral consequences, a self-consistent set of equations is formulated which describes the self-gravitating plasma of scalar charged particles. It was obtained the corresponding closed cosmological model which also was numerically simulated for the case of one-component degenerated Fermi gas and two-component Boltzmann System. It was shown that results depend weakly on the choice of a Statistical model. Two specific features of cosmological evolution of a Statistical System of scalar charged particles were obtained with respect to cosmological evolution of the minimal interaction models: appearance of giant bursts of invariant cosmological acceleration Ω at the time interval 8⋅103–2⋅104 tPl and strong heating (3–8 orders of magnitude) of a Statistical System at the same times. The presence of such features can modify the quantum theory of generation of cosmological gravitational perturbations.

  • cosmological evolution of Statistical System of scalar charged particles
    arXiv: General Relativity and Quantum Cosmology, 2014
    Co-Authors: Yurii Ignatev, Alexander Agathonov, Mikhail Mikhailov, Dmitry Ignatyev
    Abstract:

    In the paper we consider the macroscopic model of plasma of scalar charged particles, obtained by means of the Statistical averaging of the microscopic equations of particle dynamics in a scalar field. On the basis of kinetic equations, obtained from averaging, and their strict integral consequences, a self-consistent set of equations is formulated which describes the self-gravitating plasma of scalar charged particles. It was obtained the corresponding closed cosmological model which also was numerically simulated for the case of one-component degenerated Fermi gas and two-component Boltzmann System. It was shown that results depend weakly on the choice of a Statistical model. Two specific features of cosmological evolution of a Statistical System of scalar charged particles were obtained with respect to cosmological evolution of the minimal interaction models: appearance of giant bursts of invariant cosmological acceleration $\Omega$ at the time interval $8\cdot10^3\div2\cdot10^4 t_{Pl}$ and strong heating ($3÷8$ orders of magnitude) of a Statistical System at the same times. The presence of such features can modify the quantum theory of generation of cosmological gravitational perturbations.

Ibrahim Sidi Zakari - One of the best experts on this subject based on the ideXlab platform.

  • Linking Statistical literacy and data stewardship in Public Universities of Niger: Lessons learned from the collaboration with the national statistics institute
    Statistical Journal of the IAOS, 2020
    Co-Authors: Ibrahim Sidi Zakari
    Abstract:

    This paper aims at highlighting the lessons learned from recent initiatives between public universities of Niger and the national statistics institute. Our investigation of the existing national Statistical System revealed the need to increase the number of qualified human resources with advanced skills in open data, big data, data visualisation, machine learning, mathematical modeling and data-driven innovations. Moreover, the existing Statistical literacy and data crowdsourcing activities need to be validated and upscaled; and we have found a lack of experience in managing big data and in the development of mathematical methods and fast computational algorithms to analyze them. Finally, the aforementioned collaboration can be improved by working closely with private sector, civil society and the data science community to generate new approaches to emerging issues including climate change and sustainable development.

Yoshikazu Yamamoto - One of the best experts on this subject based on the ideXlab platform.

  • A Procedural and Object-Oriented Statistical Scripting Language
    Computational Statistics, 2002
    Co-Authors: Ikunori Kobayashi, Takeshi Fujiwara, Junji Nakano, Yoshikazu Yamamoto
    Abstract:

    This paper describes the language for a Statistical System named Jasp (JAva based Statistical Processor). Even if a Statistical System has an advanced graphical user interface for operations, a language for it is still important in order to have complete control of it. The language is also used to implement new Statistical procedures that are not realized in the System. For simplifying these, the Jasp language is designed as a procedural function-based scripting language especially for Statistical analysis. The language, at the same time, can treat class-based objects for gathering related functions without difficulty. In addition, it can “glue” Java classes and routines written in native languages, and make them available simply.

  • COMPSTAT - Representing Knowledge in the Statistical System Jasp
    Compstat, 2002
    Co-Authors: Ikunori Kobayashi, Yoshikazu Yamamoto, Takeshi Fujiwara
    Abstract:

    We describe a framework to assist processes of analyzing data in our Statistical System Jasp. Recent Statistical Systems provide so many Statistical methods that most users have difficulties to master how to use them properly. In addition, users are sometimes in danger of swallowing results from Systems without thinking deeply. In order to prevent these problems, we have implemented rules of “condition - action” forms in Jasp classes to express heuristic knowledge for Statistical analysis. By using these rules, Jasp can give advice to users about possible Statistical analysis procedures and notify problems when they appear. This ability is useful for users, especially for students and novices in statistics or the Jasp System.

  • A mixed user interface for a Statistical System
    2001
    Co-Authors: Yoshikazu Yamamoto, Junji Nakano, Takeshi Fujiwara, Ikunori Kobayashi
    Abstract:

    A user interface is one of the most important factor's for deciding the usefulness of a Statistical System. Nowadays, a graphical user interface (GUI) is popular because it is easy and intuitive to use. A character user interface (CUI) is, however, still important for using full abilities of the System by writing Statistical programs in order to perform complicated Statistical analyses which have not been realized in the System. We propose a mixed user interface for utilizing a GUI and a CUI alternatively and seamlessly, and consider its required characteristics. We also explain an implementation of the mixed user interface of the Statistical System Jasp (Java based Statistical processor), which is written in the Java language and adopts many recently developed computer technologies.