IDEAS home Printed from https://ideas.repec.org/a/bpj/ecqcon/v25y2010i1p43-64n5.html
   My bibliography  Save this article

On New Perspectives for Statistical Computing in Business and Industry – A Solution with STATISTICA and R

Author

Listed:
  • Weiß Christian H.

    (Darmstadt University of Technology, Department of Mathematics, Schlossgartenstraße 7, 64289 Darmstadt, Germany. E-mail: weiss@mathematik.tu-darmstadt.de)

Abstract

Companies in business and industry often make very different demands on statistical software packages, like flexibility concerning customized solutions, possibility of integrating non-standard stochastic approaches, use to validated applications, user-friendly interface, moderate costs, and many more. Usually, it is not possible to find a single software package that satisfies all such demands. Therefore, it would be attractive for entrepreneurs and statistical consultants if a collaboration among statistical software packages (e.g., leading commercial package extended by open source system) could be realized easily.In this article, we show how statistical procedures offered by R are easily integrated into the graphical user interface of STATISTICA, using the R DCOM Server of [Baier and Neuwirth, R/Scilab (D)COM Server V 3.0-1B5, 2008] and STATISTICA Visual Basic (SVB). We present solutions for different versions of STATISTICA, and illustrate all these approaches by an example from time series analysis: Using the tseries package of [Trapletti and Hornik, The tseries Package, Version 0.10-18, 2009], we tune STATISTICA with R by integrating R's ability for fitting GARCH models to given data into the user interface of STATISTICA.

Suggested Citation

  • Weiß Christian H., 2010. "On New Perspectives for Statistical Computing in Business and Industry – A Solution with STATISTICA and R," Stochastics and Quality Control, De Gruyter, vol. 25(1), pages 43-64, January.
    • Handle: RePEc:bpj:ecqcon:v:25:y:2010:i:1:p:43-64:n:5
    DOI: 10.1515/eqc.2010.004
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/eqc.2010.004
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/eqc.2010.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Thomas Baier & Erich Neuwirth, 2007. "Excel :: COM :: $$\mathsf{R}$$," Computational Statistics, Springer, vol. 22(1), pages 91-108, April.
    2. Bera, Anil K & Higgins, Matthew L, 1993. "ARCH Models: Properties, Estimation and Testing," Journal of Economic Surveys, Wiley Blackwell, vol. 7(4), pages 305-366, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dankenbring, Henning, 1998. "Volatility estimates of the short term interest rate with an application to German data," SFB 373 Discussion Papers 1998,96, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Pierdzioch, Christian, 2000. "Noise Traders? Trigger Rates, FX Options, and Smiles," Kiel Working Papers 970, Kiel Institute for the World Economy (IfW Kiel).
    3. Sellin, Peter, 1998. "Monetary Policy and the Stock Market: Theory and Empirical Evidence," Working Paper Series 72, Sveriges Riksbank (Central Bank of Sweden).
    4. Nico Knuth & Andreas Nastansky, 2025. "Anwendung von Deep Learning in der Prognose der Volatilität des DAX: Ein Vergleich der Prognosegüte von GARCH und LSTM," Statistische Diskussionsbeiträge 59, Universität Potsdam, Wirtschafts- und Sozialwissenschaftliche Fakultät.
    5. Worthington, Andrew & Kay-Spratley, Adam & Higgs, Helen, 2005. "Transmission of prices and price volatility in Australian electricity spot markets: a multivariate GARCH analysis," Energy Economics, Elsevier, vol. 27(2), pages 337-350, March.
    6. Eleni Constantinou & Robert Georgiades & Avo Kazandjian & George Kouretas, 2005. "Mean and variance causality between the Cyprus Stock Exchange and major equity markets," Working Papers 0501, University of Crete, Department of Economics.
    7. W. K. Li & Shiqing Ling & Michael McAleer, 2001. "A Survey of Recent Theoretical Results for Time Series Models with GARCH Errors," ISER Discussion Paper 0545, Institute of Social and Economic Research, The University of Osaka.
    8. Pierre Giot & Sébastien Laurent, 2003. "Value-at-risk for long and short trading positions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(6), pages 641-663.
    9. Chimilila, Cyril, 2017. "Forecasting Tax Revenue and its Volatility in Tanzania," African Journal of Economic Review, African Journal of Economic Review, vol. 5(01), January.
    10. McMillan, David G. & Speight, Alan E. H., 2001. "Non-ferrous metals price volatility: a component analysis," Resources Policy, Elsevier, vol. 27(3), pages 199-207, September.
    11. Bollerslev, Tim & Ghysels, Eric, 1996. "Periodic Autoregressive Conditional Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(2), pages 139-151, April.
    12. Imke Brüggemann & Dieter Nautz, 1997. "Money growth volatility and the demand for money in Germany: Friedman’s volatility hypothesis revisited," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 133(3), pages 523-537, September.
    13. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    14. Dhaoui, Elwardi, 2013. "What we have learnt from financial econometrics modeling?," MPRA Paper 63843, University Library of Munich, Germany.
    15. Sandmann, G. & Koopman, Siem, 1996. "Maximum likelihood estimation of stochastic volatility models," LSE Research Online Documents on Economics 119161, London School of Economics and Political Science, LSE Library.
    16. Gianluigi Pelloni & Wolfgang Polasek, 2003. "Macroeconomic Effects of Sectoral Shocks in Germany, The U.K. and, The U.S. A VAR-GARCH-M Approach," Computational Economics, Springer;Society for Computational Economics, vol. 21(1), pages 65-85, February.
    17. Mahua Barari & Nityananda Sarkar & Srikanta Kundu & Kushal Banik Chowdhury, 2014. "Forecasting House Prices in the United States with Multiple Structural Breaks," International Econometric Review (IER), Econometric Research Association, vol. 6(1), pages 1-23, April.
    18. ROCKINGER, Michael & JONDEAU, Eric, 2000. "Conditional Volatility, Skewness, and Kurtosis : Existence and Persistence," HEC Research Papers Series 710, HEC Paris.
    19. Pedro Hugo Clavijo Cortes, 2017. "Balance comercial y volatilidad del tipo de cambio nominal: Un estudio de series de tiempo para Colombia," Revista Economía y Región, Universidad Tecnológica de Bolívar, vol. 11(1), pages 37-58.
    20. BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:ecqcon:v:25:y:2010:i:1:p:43-64:n:5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyterbrill.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.