Jeffrey

Because there is no time in logic.

As you can see mathematics and logic have a lot in common, however, in terms of notation there are some obvious differences. Logic usually doesn't reference quantity apart from a sort of singular operator.

In short, Von Neumann & Morgenstern are compressed in the writing of John Forbes Nash (who writes n-tuple theory) for a tuple (reduced by Kakutani).

In other words, Barry Greenstein is correct. There is no time in logic, and mathematics is idiotic.

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I've been working on this particular piece for years. It belonged to James Bond's dad (codename: Zeus); (codename: Delos).



You probably recall this iconic scene. Although, critics contest that James Bond cannot die because he is a superhero.

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edit: How does this apply to poker? The solution is surprisingly simple. We don't need statistics and should know the answer anyway. Later we will look at some properties of Markov Chains and Martingale difference sequences before concluding that actions made in the moment are made regardless of statistical updates.

In short, we want to reduce a panel data to time series--eliminate time series altogether--and then simply evaluate the properties of our argument. Now there is only cross-sectional data and the time series element is gone altogether. Eventually, we could dispense with statistics itself by simply considering what econometricians call the corner solution and elasticity.



Years ago I got help on this math problem from DrThundza. For those interested, it's time for me to tackle the problem using modern computer technology.



edit: so, I'm getting ready to solve the problem.

The first and most obvious solution is to use an annihilation matrix to eliminate one aspect of the data (which I already have). Then by using a simple intersection algorithm a polygon can be fit to the object.



The second, less obvious method, is simply to use polyfit and "eyeball" the solution by comparing areas.

Here is 1 solution: What else would you do?





I uploaded a covert description of everything ever. Based on the well known transformation, an orthodox transformation of reality onto the R1 plane (0,1) a complete description of everything ever is here.



Reinstate the original matrices as bootstrapped samples (including a sort of random information theory x-axis bootstrap for the independent variable)





We're including some random values as a backdrop for "this is everything there is." Amazingly, everything there is changes dramatically as we bootstrap more data into our work.

What seems to be fun here is we are using a sort of arbitrary covariance determinant to evaluate the y-axis for compression.

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