Thank you very much guys :)
bpet, yes those numbers seem to match the simulations quite precisely. More simple math than I expected :) Here's what those formulas give:
P Q X>Y X=Y Equity
0.8 0.6 0.32 0.56 0.6
0.7 0.4 0.42 0.46 0.65
That's almost exactly the simulation numbers.
I'm having...
If two binomially distributed variables are generated as paired events, how often will the variable with p=X be greater than the variable with p=Y? Also what is the "equity" if ties are counted as .5 for each?
For instance in Excel I generated 10,000 numbers with p=.8 and 10,000 with p=.6...
Say you have something like f(x)*(f(y)+f(z)). What are the partial derivatives with respect to each variable? What rules are involved?
And how would this differ from f(x)*(g(x)+h(x)).
I'm having a problem trying to use the Levenberg-Marquardt source code from Numerical Recipes in C. The code requires the gaussj(float**, int, float**, int) function, and according to:
http://www.fizyka.umk.pl/nrbook/c0-2.pdf
That is found in section 2.1. However, the...
Does a http://en.wikipedia.org/wiki/Tikhonov_regularization" solution for least squares have to be iteratively solved? Or is there a way to perform regularization via linear algebra, the way linear regression can be done by solving the (XTX)B=XTy normal equations?
Thank you, that might be helpful.
Anyone know of algorithmic pseudocode for least squares anywhere, that I myself could use to create code? A http://en.wikipedia.org/wiki/Linear_regression#Example" can be estimated by solving for the (XTX)B=XTy normal equations, but that seems to be different...
I actually already have LAPACK++ installed, however it's really pretty complicated. I'd like some simpler code that I can modify, for instance to implement regularization.