Skip to main content
SpringerLink
Log in

Parallel computing in the statistical system Jasp

  • Original Paper
  • Published:
Computational Statistics Aims and scope Submit manuscript

Abstract

Modern statistical data analysis often requires powerful computers. Parallel computing is a technique to realize such a computer system. Although many “low-level” software technologies for parallel computing have been developed, they are not easy to use for statisticians who are accustomed to “high-level” statistical languages. In this paper, we describe high-level parallel computing functions in a statistical analysis system called Jasp. We implemented them mainly considering ease of use.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Davison AC, Hinkley DV (1997) Bootstrap methods and their application. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  • Flenner R (2001) Jini and JavaSpaces application development. Indiana, Sams Publishing

    Google Scholar 

  • Fujiwara T, Nakano J, Yamamoto Y, Kobayashi I (2001) An implementation of a statistical language based on Java. J Jpn Soc Comput Stat 14(1): 59–67

    Google Scholar 

  • Geist A, Beguelin A, Dongarra J, Jiang W, Manchek R, Snuderam V (1994) PVM: parallel virtual machine. A user’s guide and tutorial for networked parallel computing. The MIT Press, Cambridge

    Google Scholar 

  • Gropp W, Lusk E, Skjellum A (1999) Using MPI: portable parallel programming with the message-passing interface. The MIT Press, Cambridge

    Google Scholar 

  • Ihaka R, Gentleman R (1996) R: a language for data analysis and graphics. J Comput Graph Stat 5: 299–314

    Article  Google Scholar 

  • Li MN, Rossini AJ (2001) RPVM: Cluster statistical computing in R. R News 1(3): 4–7

    Google Scholar 

  • Nakano J, Fujiwara T, Yamamoto Y, Kobayashi I (2000) A statistical package based on pnuts. COMPSTAT2000 proceedings in computational statistics. Physica-Verlag, Heidelberg, pp 361–366

  • Rossini A, Tierney L, Li MN (2003) Simple parallel statistical computing in R. UW Biostatistics working paper series, Paper 193, University of Washington. (http://www.bepress.com/uwbiostat/paper193)

  • Yamamoto Y, Nakano J (2002) Distributed processing functions of a time series analysis system. J Jpn Soc Comput Stat 15(1): 65–77

    MathSciNet  Google Scholar 

  • Yu H (2002) Rmpi: Parallel statistical computing in R. R News 2(2): 10–14

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Tokushima Bunri University, 1314-1 Shido, Sanuki-shi, Kagawa, 769-2193, Japan

    Yoshikazu Yamamoto

  2. The Institute of Statistical Mathematics and the Graduate University for Advanced Studies, 4-6-7 Minami-Azabu, Minato-ku, Tokyo, 106-8569, Japan

    Junji Nakano

  3. Tokyo University of Information Sciences, 1200-2 Yatoh-cho, Wakaba-ku, Chiba, 265-8501, Japan

    Takeshi Fujiwara

Authors
  1. Yoshikazu Yamamoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Junji Nakano
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Takeshi Fujiwara
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yoshikazu Yamamoto.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Yamamoto, Y., Nakano, J. & Fujiwara, T. Parallel computing in the statistical system Jasp. Comput Stat 25, 291–298 (2010). https://doi.org/10.1007/s00180-009-0176-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00180-009-0176-6

Keywords

Search

Navigation