Dance Steps : A Statistical Quantification of Data Pair Similarities

Herein we attempt to quantify Tom McClellan’s notion of Dance Steps between two series of data, often of differing time periods (a current, or dependent and a previous, or independent period data series), looking for similarities in the turning points to use as a reference for the future turning points and direction of the current period data series. The visual recognition of dance steps requires a fuzzy relationship between the time difference and degree differences of turning points that loosely correspond in time. We discuss a means of measuring this on the same scale as correlation where perfect matching equates to a metric of +1, no match to 0, and perfect inverse matching to-1

MoreLess

Year of publication:	2022
Authors:	Vince, Ralph
Publisher:	[S.l.] : SSRN
Subject:	Statistische Methode \| Statistical method \| Statistische Methodenlehre \| Statistical theory \| Theorie \| Theory \| Statistik \| Applied statistics

freely available

Full text |

More access options

doi.org

Check Google Scholar

In German libraries (KVK)

I need help

Which error do you want to report?

Report: URL of this record is broken

Please note: Sometimes more than one URL is available for a resource. Please click on "More Options" to display these URLs

Report: Addition of an URL to that resource

Please note: Sometimes more than one URL is available for a resource. Please click on "More Options" to display these URLs

Report: The language(s) of that resource is/are…

Please note: Required language not in the list? Please use comment field

Report: Addition of an identifier to that resource

Report: report typo

Report: Add statement

Report: Add keywords

Please use the commentary box to describe other errors

Would you like to receive a feedback?

Commentary

Please type the code from the image

For general questions please use this address.

Persistent link: https://www.econbiz.de/10014078932