Privacy Statement

R&R Consulting has created this privacy statement in order to demonstrate our firm commitment to your privacy. The following discloses our information gathering and dissemination practices for this web-site: and

We use your IP address to help diagnose problems with our server and to administer our web site. Additionally, IP addresses are used to obtain aggregate visitor information concerning their use of our web site.

We do not link IP addresses to any personally identifiable information. Therefore, you remain anonymous when you browse our web site. Our web server collects information such as number of visits, average time spent on the site, pages viewed, etc., but this information is not traceable back to an individual user. We use this information to analyze how visitors use our web site and to generate ideas on how it might be improved.

This site contains links to other sites. R&R Consulting is not responsible for the privacy practices or the content of such Web sites. R&R Consulting does not share the information it collects with its partners.

Our site provides an email address for you to request information about the company, its products and its services, or to have someone contact you. Contact information from the email address form is used to send information about our company to you and to get in touch with you when necessary.

Contacting us

If you have any questions about this privacy statement, the practices of this site, or your dealings with this Web site, you can contact us at the address below:

R&R Consulting
6 East 46th Street, Ste. 200
New York, NY 10017 USA


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Automatic Synthesis of Tri-Diagonal Markov Transition Matrices: A Failure of the Inverse Ferron-Frobenius AlgorithmABSTRACT: Sylvain Raynes experimented with a method developed by Goya and Boyarski (1993) to standardize the synthesis of conditional Markov transition matrices for deal entry in our automated re-rating system, ABSTRAK®. In the analytical literature, the reverse-engineering of a Markov matrix from its spectral-radius eigenvector is referred to as the Inverse Perron-Frobenius Problem. Our analysts do this synthesis manually, so a successful outcome […]

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