Posts Tagged ‘modeling’

In case you ever wanted to see some nice theory + simulation + visuals here’s a collection of nice Mathematica based explorations:

Animation for Epidemic Spread

Animation for Epidemic Spread

Jeff Bryant with Ed Pegg’s code on Influenza Epidemic modeling

Disease spread demonstration

SARs spread demonstration/animation

Oh, and I thought this was interesting… a nice PPT on pandemics.

I wonder if the swine flu spread through social networks with a similar dynamic? hmmm… Perhaps one should dig through this code for mining Twitter with Mathematica and start connecting the dots.  How could we do this?  We need to pull down a lot of tweets.  and we need some way to codify them by location or friends/groups.  What would we consider “spreading”.  Is it posting a link? replying to someone? hmmm.  Maybe this is a big fat waste of time….

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The news is a maniacal scramble to make sense of the current financial situation around the world.

Predictions, ____ expert from _____ investment research firm, advice, soothsaying, modeling, bear vs. bull, Fed should do this, Fed shouldn’t do this…. and so on.

A truth I got comfortable with a long time ago but had reinforced over the last three weeks in my life.

Your model can only be as predictive as the thing you are modeling.

– Jason Cawley, Wolfram Research (and probably others…)

That’s a stupid statement, right? Duh.  I know that.

Really think about it though.  and then consider these things and your interpretation of them

  • weather forecasts
  • endless dow jones index reports
  • Political polls
  • compatibility tests in online dating
  • SAT scores
  • TSA profiling at airports
  • Annual budgeting for businesses
  • Or go through the latest in the news

All of these “indicators” attempt to predict complex systems/situations.  Those systems have to show some stability, some simplicity to ever give way to useful prediction (useful = do you get info you can use elsewhere and with enough time/energy to use it).

There is potential to get some local or short term prediction due to local or short term stability.  However, to effectively use that over time you need to be able to predict when that stability yields to a new pattern. That is where it gets difficult.

Yes, you can aggregate a lot of these indicators to produce some sort of statistical sample.  Usually though, you’re simply hiding the intesting stuff in the errors in your statistical model.  Washing out the outliers as “noise”.  The problem is, especially in the indicators above, it’s the outliers that matter! But I digress…

Point for financial pundits: national and global economics itself is complex. no simple model, simple statement, simple index can accurately model it. not even poorly.

Agree or Disagree?  Let’s have a discussion.

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