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But more importantly, has no one used the Hopscotch method (is claimed 3-4 times faster than ADI). And it is unconditionally stable, 2nd order accurate. Easy to program.

Statistics: Posted by Cuchulainn — November 19th, 2017, 9:11 pm

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Cuchulainn wrote:ppauper wrote:the first thing I noticed was the typo, Dataism Education

Next time iI will fill that bio stuff in myself _before_ I send the stuff.

Anyways, I can be contacted at dduffy at dataism dot nl

To err is human.

BTW did you read the rest of the article(s)?

skimmed it

I think I vaguely know one of your references, black chick called lucy?

Campbell, L.J. and Yin, B. 2006. On the Stability of Alternating-Direction Explicit Methods for Advection-Diffusion Equations. New York: Wiley Interscience.

p49 below eqn 6, you say, "instantiating." Is that a real word?

and in (5) you use A which you don't seem to define until later in Section 4

I think you are correct. To the point article.

https://carleton.ca/math/people/lucy-campbell/

"instantiating" is kind of C++ urban jargon.

I don't normally do forward references. I'l check it out. On the other hand, 'A' is defined in the earlier paper with Alan and Paul (Paul and Alan) so i am covered to a certain extent.

Statistics: Posted by Cuchulainn — November 16th, 2017, 9:42 pm

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"M. Ryten. Practical Modelling For Limited Price Index and Related Inflation Products. InICBI Global Derivatives Conference Paris, 2007."

It seems it contains some nice ideas and I would very much like to see it. Does any of you have access to it and would be willing to share?

Thank you very much.

Statistics: Posted by zukimaten — November 16th, 2017, 11:46 am

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ppauper wrote:Cuchulainn wrote:

the first thing I noticed was the typo, Dataism Education

Next time iI will fill that bio stuff in myself _before_ I send the stuff.

Anyways, I can be contacted at dduffy at dataism dot nl

To err is human.

BTW did you read the rest of the article(s)?

skimmed it

I think I vaguely know one of your references, black chick called lucy?

Campbell, L.J. and Yin, B. 2006. On the Stability of Alternating-Direction Explicit Methods for Advection-Diffusion Equations. New York: Wiley Interscience.

p49 below eqn 6, you say, "instantiating." Is that a real word?

and in (5) you use A which you don't seem to define until later in Section 4

Statistics: Posted by ppauper — November 16th, 2017, 10:52 am

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Dataism is a new data-driven school of painting.

Dataism is a form of artistic anarchy that challenged the social, political and cultural values of the time.

We display our data driven art just opposite Fighting 69th Armory Show at Lexington and 24th.

Statistics: Posted by Cuchulainn — November 13th, 2017, 11:22 pm

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Cuchulainn wrote:

the first thing I noticed was the typo, Dataism Education

Next time iI will fill that bio stuff in myself _before_ I send the stuff.

Anyways, I can be contacted at dduffy at dataism dot nl

To err is human.

BTW did you read the rest of the article(s)?

Statistics: Posted by Cuchulainn — November 13th, 2017, 10:03 pm

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the first thing I noticed was the typo, Dataism Education

Statistics: Posted by ppauper — November 13th, 2017, 8:13 pm

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gefeliciteerd!

Hartelijk dank!

Statistics: Posted by henktijms — November 3rd, 2017, 4:08 pm

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Paperback: 535 pages

Publisher: Cambridge University Press

ISBN 978-1-108-40784-7

The book covers all of the standard material in introductory probability, but it deals also with many other topics that are usually not found in other books- such as Kelly betting, success runs, entropy and probability, Poissonization method, Markov Chain Monte Carlo Simulation (and challenging probability puzzles).

More details (table of contents, excerpt) in:

https://www.book2look.com/vbook.aspx?id=9781108407847

Statistics: Posted by henktijms — November 3rd, 2017, 12:21 pm

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[$]\begin{array}{ll}

\frac{\partial V}{\partial t} = \frac{1}{2} \sigma^{2} \left( \frac{S}{A} \right) x^{2} (1 - x)^{2} \frac{\partial^{2} V}{\partial x^{2}} + \left\{ r x (1 - x) - \sigma^{2} x^{2} (1 - x)^{2} \right\} \frac{\partial V}{\partial x}\\

\\

\;\;\;\;\;\;\;\;+ \left( \gamma (S - A) (1 - y)^{2} / b \right) \frac{\partial V}{\partial y} - r V \\

\\

0 < x < 1, \;\;\; 0 < y < 1

\left( S = \frac{ax}{1 - x}, A = \frac{by}{1 - y} \right).

\end{array}

[$]

The FDM is fine when we give the usual BS BC for x and no BC in y (just use upwinding). See artilcle.

The *question* now is: I want to use MOL so how we we specify the BC (or is it a PDE) for [$]y \in Set({{0,1}})[$]?

I have a hunch but am not saying

I would like to compare NDSolve and Boost.odeint.

Statistics: Posted by Cuchulainn — October 25th, 2017, 5:54 pm

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http://onlinelibrary.wiley.com/doi/10.1 ... 10620/epdf

Statistics: Posted by Cuchulainn — September 24th, 2017, 5:40 pm

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