Journal of the Japan Statistical Society, Japanese Issue
Online ISSN : 2189-1478
Print ISSN : 0389-5602
ISSN-L : 0389-5602
Volume 49 , Issue 2
Showing 1-5 articles out of 5 articles from the selected issue
Presidential Address
  • Shigeru Kawasaki
    Type: research-article
    2020 Volume 49 Issue 2 Pages 161-186
    Published: March 30, 2020
    Released: December 02, 2020
    JOURNALS FREE ACCESS

    This paper reviews the path of historical development of statistics and statistical science in Japan from the Meiji Restoration (1868) until the early Showa Era (mid 1930's) from a viewpoint of contribution of official statistics. It discusses the interaction of official statistics with other fields of statistics, and considers the future prospects of the relationship of official statistics with overall statistics and statistical science. Since the introduction of statistics to Japan in the early Meiji era, official statistics contributed to the development of statistics at large by providing materials and resources for statistical analysis and applications of statistical methodology. It also took roles in statistical education and training, which contributed to dissemination of statistical knowledge to the society at large and academia, as well as government institutions. Further, it gave impetus to the foundation of the statistical society. The roles of official statistics in the development of statistics and statistical science remain to be essentially the same in the present day. Those who are engaged in official statistics should continue their efforts to contribute to promotion of statistical knowledge in the society and the development of statistical science.

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Special Section: Financial Data Analysis
Special Topic: The JSS Research Prize Lecture
  • Yasumasa Matsuda
    Type: research-article
    2020 Volume 49 Issue 2 Pages 265-280
    Published: March 30, 2020
    Released: December 02, 2020
    JOURNALS FREE ACCESS

    This paper reviews Continuous time Auto-Regressive Moving Average (CARMA) models.We define CARMA models as a natural extension of discrete time ARMA models through state space representations. After the continuous time extension to CARMA models, we introduce the causal stationary conditions, derive the explicit forms of covariance and spectral density functions, show the joint distributions and examine the second order properties of regularly sampled CARMA processes. Finally, we review two empirical applications to high frequency data of exchange rates and Brookhaven turbulence data. The contents of the paper are based on the presentation slides of Professor Peter Brockwell for his plenary session in Japanese Joint Statistical Meeting at Shiga University in 2019.

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