IDEAS home Printed from https://ideas.repec.org/p/mcm/deptwp/2024-11.html
   My bibliography  Save this paper

Quarto the Assassin

Author

Listed:
  • Jeffrey S. Racine

Abstract

My interest in open source research tools has a long arc, and the tools I adopt evolve as new and improved approaches surface (Racine and Hyndman 2002; Meredith and Racine 2009; Racine 2012). A recent development brings to mind overused superlatives like “game-changer”, among others, and I suspect you will agree “100%” that one recent development belongs in either the “Assassin” or “Saturn” category, or perhaps both (the latter being associated with consuming one’s progeny as prophecy had it that Saturn would be overthrown by one of his sons, so in response, he devoured them upon birth). In this Chapter we examine how Quarto can be used to create dynamic reveal.js presentations that are simply unrivalled, anywhere, period (“100%”, a “game-changer”). As such, and particularly for those accustomed to the Beamer slide format, the adoption of these new tools may be of particular interest. This document, naturally, is authored in Quarto, and the Quarto script for this document and the reveal.js slides discussed below are available at https://github.com/JeffreyRacine/rch.

Suggested Citation

  • Jeffrey S. Racine, 2024. "Quarto the Assassin," Department of Economics Working Papers 2024-11, McMaster University.
    • Handle: RePEc:mcm:deptwp:2024-11
    as

    Download full text from publisher

    File URL: http://socialsciences.mcmaster.ca/econ/rsrch/papers/archive/2024-11.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tong Zeng & R. Carter Hill, 2020. "Stein-rule estimation in genetic carrier testing," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 10(2), pages 111-128.
    2. Hill, R Carter & Cartwright, P A, 1994. "The Statistical Properties of the Equity Estimator," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 141-147, April.
    3. Hill, R Carter & Cartwright, P A, 1994. "The Statistical Properties of the Equity Estimator: A Rejoinder," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 155-155, April.
    4. Kim, Minbo & CarterHill, R., 1995. "Shrinkage estimation in nonlinear regression The Box-Cox transformation," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 1-33.
    5. William E. Griffiths & R. Carter Hill, 2022. "On the Power of the F-test for Hypotheses in a Linear Model," The American Statistician, Taylor & Francis Journals, vol. 76(1), pages 78-84, January.
    6. Carter Hill, R. & Judge, George, 1987. "Improved prediction in the presence of multicollinearity," Journal of Econometrics, Elsevier, vol. 35(1), pages 83-100, May.
    7. Evan Meredith & Jeffrey S. Racine, 2009. "Towards reproducible econometric research: the Sweave framework," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(2), pages 366-374, March.
    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. Fok, Dennis & Franses, Philip Hans, 2001. "Forecasting market shares from models for sales," International Journal of Forecasting, Elsevier, vol. 17(1), pages 121-128.
    2. Lu, Huidi & van der Lans, Ralf & Helsen, Kristiaan & Gauri, Dinesh K., 2023. "DEPART: Decomposing prices using atheoretical regression trees," International Journal of Research in Marketing, Elsevier, vol. 40(4), pages 781-800.
    3. S. Hossain & S. Ejaz Ahmed & Grace Y. Yi & B. Chen, 2016. "Shrinkage and pretest estimators for longitudinal data analysis under partially linear models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(3), pages 531-549, September.
    4. Wan, Alan T. K. & Chaturvedi, Anoop, 2001. "Double k-Class Estimators in Regression Models with Non-spherical Disturbances," Journal of Multivariate Analysis, Elsevier, vol. 79(2), pages 226-250, November.
    5. Valérie Orozco & Christophe Bontemps & Élise Maigné & Virginie Piguet & Annie Hofstetter & Anne Marie Lacroix & Fabrice Levert & Jean-Marc Rousselle, 2017. "How to make a pie? Reproducible Research for Empirical Economics & Econometrics," Post-Print hal-01939942, HAL.
    6. S. K. Sapra, 2003. "Pre-test estimation in Poisson regression model," Applied Economics Letters, Taylor & Francis Journals, vol. 10(9), pages 541-543.
    7. Adkins, Lee C & Krehbiel, Timothy & Hill, R Carter, 2000. "Using Cointegration Restrictions to Improve Inference in Vector Autoregressive Systems," Review of Quantitative Finance and Accounting, Springer, vol. 14(2), pages 193-208, March.
    8. Čížek, Pavel, 2004. "(Non) Linear Regression Modeling," Papers 2004,11, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    9. Cao, Ming-Xiang & He, Dao-Jiang, 2017. "Admissibility of linear estimators of the common mean parameter in general linear models under a balanced loss function," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 246-254.
    10. Wenxing Guo & Xiaohui Liu & Shangli Zhang, 2016. "The principal correlation components estimator and its optimality," Statistical Papers, Springer, vol. 57(3), pages 755-779, September.
    11. R. Carter Hill & Tong Zeng, 2014. "Shrinkage Estimation in the Random Parameters Logit Model," Departmental Working Papers 2014-11, Department of Economics, Louisiana State University.
    12. Eric Hillebrand & Tae-Hwy Lee, 2012. "Stein-Rule Estimation and Generalized Shrinkage Methods for Forecasting Using Many Predictors," Advances in Econometrics, in: 30th Anniversary Edition, pages 171-196, Emerald Group Publishing Limited.
    13. Zhang, Xinyu & Chen, Ti & Wan, Alan T.K. & Zou, Guohua, 2009. "Robustness of Stein-type estimators under a non-scalar error covariance structure," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2376-2388, November.
    14. Valérie Orozco & Christophe Bontemps & Elise Maigné & Virginie Piguet & Annie Hofstetter & Anne Lacroix & Fabrice Levert & Jean‐Marc Rousselle, 2020. "How To Make A Pie: Reproducible Research For Empirical Economics And Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 34(5), pages 1134-1169, December.
    15. Michael S. Delgado & Christopher F. Parmeter, 2013. "Embarrassingly Easy Embarrassingly Parallel Processing in R: Implementation and Reproducibility," Working Papers 2013-06, University of Miami, Department of Economics.
    16. McMillen, Daniel & O’Sullivan, Arthur, 2013. "Option value and the price of teardown properties," Journal of Urban Economics, Elsevier, vol. 74(C), pages 71-82.

    More about this item

    Keywords

    Quarto;

    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:mcm:deptwp:2024-11. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/demcmca.html .

    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.