IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/8fjn7.html
   My bibliography  Save this paper

Random Coil Statistics: : A Vector Model

Author

Listed:
  • DATTA, JAYDIP

    (The Institution of Chemist ( India ) , Kolkata , 700017)

Abstract

In our earlier research MATHEMATICAL STATISTICS: AN APPLICATION BASED STATISTICS (RG) December 2019 , ( Jaydip Datta , Nino Durglishvili ) we have worked on application based statistics related to RANDOM COIL STATISTICS . The present Work wishes to NOTE some key features of Statistics of Randomness like VECTOR or Random Walk (Zigzag) Statistics. The primary Probability Distribution F ( X ) of a Random Chain is described as a Gaussian Function. The variance can be expressed in terms a Square Matrix called co-variance matrix. This approach is purely Qualitative / Theoretical Statistics. The hydrodynamic data can be analysed by polynomial regression approach. The co-variance for regression data signifies a Square Matrix representationVECTOR or Random Walk (Zigzag) Statistics. REF : slideplayer.com ( Figure Source )

Suggested Citation

  • Datta, Jaydip, 2020. "Random Coil Statistics: : A Vector Model," OSF Preprints 8fjn7, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:8fjn7
    DOI: 10.31219/osf.io/8fjn7
    as

    Download full text from publisher

    File URL: https://osf.io/download/5eb44390a2199500cc5d35aa/
    Download Restriction: no

    File URL: https://libkey.io/10.31219/osf.io/8fjn7?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:8fjn7. 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.