[Japanese/English]

The Institute of Statistical Mathematics

October 2, 2023 (Ver. 1.3.8-4)



1. Introduction

　The TIMSAC (TIMe Series Analysis and Control) is a general program package for analysis, prediction and control of time series and has been developed at the Institute of Statistical Mathematics. The original TIMSAC or TIMSAC-72 was published in Akaike and Nakagawa (1972). After that, TIMSAC-74, TIMSAC-78 and TIMSAC-84 were published as the TIMSAC series in Computer Science Monograph. Many programs in the TIMSAC series were developed to provide procedures for analyzing practical data, e.g., optimal control of an industrial process, analysis of economic fluctuations and so on. In this package several information criteria are used for model selection. In TIMSAC-72, FPE (Final Prediction Error) is used. After TIMSAC-74, AIC (Akaike Information Criterion) is used for model selection. TIMSAC-78 contains several programs based on Bayesian modeling where ABIC (Akaike Bayesian Information Criterion) is also used for model selection.

　R is a free programming language or an environment that includes many statistical techniques. R has facilities for data manipulation on arrays and matrices, graphic and foreign language interfaces. The programs of the TIMSAC series are written in FORTRAN. We provide timsac R package in order to use procedures of part of programs of the TIMSAC series from R. If necessary some functions display statistical analysis results using R graphics functions.

　The most popular function in this package, decomp(), is also available as a web application RS-Decomp using Shiny.


2. Package installation

　We provide the source files of the package and the binary files for Windows. They have been tested on Windows 11 (R-4.3.1) and Ubuntu 22.04 LTS (R-4.3.1). The timsac package has been registered as a CRAN Contributed Package, available for download from this web site .

2.1 Installation on Windows
  1. Put timsac_1.3.8-4.zip in a suitable directory, then start R (RGui).

  2. From the RGui [Packages] menu
    　　　–> Install package(s) from local zip files…
    　　　–> Select files
    　　　–> timsac_1.3.8-4.zip
    3. 　
  3. From the RGui [Packages] menu
    　　　–> Load Package…
    　　　–> Select one
    　　　–> timsac
2.2 Installation on Linux
  1. Put the source package timsac_1.3.8-4.tar.gz in a suitable directory and install it from the command line with

    　　# R CMD INSTALL timsac_1.3.8-4.tar.gz 　

  2. You can use the timsac package with the following code within R:

    　　> library(timsac)

The reference manual timsac-manual.pdf is available here.
For more information about functional models and information criteria, see timsac_guide_j.pdf (in Japanese) or timsac_guide_e.pdf (in English) in the doc subdirectory of the timsac package.

3. Reference

[1] H. Akaike, E. Arahata, T. Ozaki (1975-1976). TIMSAC-74, A Time series analysis and control program package (1) & (2), Computer Science Monographs, No.5 & 6, The Institute of Statistical Mathematics, Tokyo.

[2] H. Akaike, G. Kitagawa, E. Arahata, F. Tada (1979). TIMSAC-78, Computer Science Monographs, No.11, The Institute of Statistical Mathematics, Tokyo.

[3] H. Akaike, T. Ozaki, M. Ishiguro, Y. Ogata, G. Kitagawa, Y.-H. Tamura, E. Arahata, K. Katsura, Y. Tamura (1985). TIMSAC-84 Part 1 & Part 2, Computer Science Monographs, No.22 & 23, The Institute of Statistical Mathematics, Tokyo.

[4] H. Akaike and T.Nakagawa (1988). Statistical Analysis and Control of Dynamic Systems, Kluwer Academic publishers.

Please send comments and bug reports to ismrp(at)grp.ism.ac.jp.