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REGCMPNT A Fortran Program for Regression Models with ARIMA Component Errors

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  • Bell, William R.

Abstract

RegComponent models are time series models with linear regression mean functions and error terms that follow ARIMA (autoregressive-integrated-moving average) component time series models. Bell (2004) discusses these models and gives some underlying theoretical and computational results. The REGCMPNT program is a Fortran program for performing Gaussian maximum likelihood estimation, signal extraction, and forecasting with RegComponent models. In this paper we briefly examine the nature of RegComponent models, provide an overview of the REGCMPNT program, and then use three examples to show some important features of the program and to illustrate its application to various different RegComponent models.

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  • Bell, William R., 2011. "REGCMPNT A Fortran Program for Regression Models with ARIMA Component Errors," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 41(i07).
    • Handle: RePEc:jss:jstsof:v:041:i07
    DOI: http://hdl.handle.net/10.18637/jss.v041.i07
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    References listed on IDEAS

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    1. Commandeur, Jacques J. F. & Koopman, Siem Jan & Ooms, Marius, 2011. "Statistical Software for State Space Methods," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 41(i01).
    2. McElroy, Tucker, 2008. "Matrix Formulas For Nonstationary Arima Signal Extraction," Econometric Theory, Cambridge University Press, vol. 24(4), pages 988-1009, August.
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    Cited by:

    1. Gómez, Victor, 2015. "SSMMATLAB: A Set of MATLAB Programs for the Statistical Analysis of State Space Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 66(i09).
    2. repec:jss:jstsof:41:i01 is not listed on IDEAS
    3. repec:jss:jstsof:41:i06 is not listed on IDEAS

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