IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/fzqxv_v1.html
   My bibliography  Save this paper

mcp: An R Package for Regression With Multiple Change Points

Author

Listed:
  • Lindeløv, Jonas Kristoffer

Abstract

The R package mcp does flexible and informed Bayesian regression with change points. mcp can infer the location of changes between regression models on means, variances, autocorrelation structure, and any combination of these. Prior and posterior samples and summaries are returned for all parameters and a rich set of plotting options is available. Bayes Factors can be computed via Savage-Dickey density ratio and posterior contrasts. Cross-validation can be used for more general model comparison. mcp ships with sensible defaults, including priors, but the user can override them to get finer control of the models and outputs. The strengths and limitations of mcp are discussed in relation to existing change point packages in R.

Suggested Citation

  • Lindeløv, Jonas Kristoffer, 2020. "mcp: An R Package for Regression With Multiple Change Points," OSF Preprints fzqxv_v1, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:fzqxv_v1
    DOI: 10.31219/osf.io/fzqxv_v1
    as

    Download full text from publisher

    File URL: https://osf.io/download/5e125334573419015f80355f/
    Download Restriction: no

    File URL: https://libkey.io/10.31219/osf.io/fzqxv_v1?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
    ---><---

    More about this item

    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:osf:osfxxx:fzqxv_v1. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    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.