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Re:Forecasting s-curves is hard by ignoramous on Sunday April 19, 2020 @05:14PM (#22918849)
> I don’t understand what you’re saying.

I think what GP means is, leaving it upto professionals alone is a recipe for disaster because of the inherent corruption, greed, biases, and prejudices at play.

> So what are you advocating?

Not speaking for GP, but simpler models are more likely to be a good approximation and more than enough, anyway [0]? Simplicity helps because it stops the pundits and politicians from sort of running away with it?

[0] Newton's theory of gravitation has been supplanted by Einstein's theory of relativity and yet Newton's theory remains generally "empirically adequate". Indeed, Newton's theory generally has excellent predictive power. Yet Newton's theory is not an approximation of Einstein's theory. For illustration, consider an apple falling down from a tree. Under Newton's theory, the apple falls because Earth exerts a force on the apple—what is called "the force of gravity". Under Einstein's theory, Earth does not exert any force on the apple. Hence, Newton's theory might be regarded as being, in some sense, completely wrong but extremely useful (The usefulness of Newton's theory comes partly from being vastly simpler, both mathematically and computationally, than Einstein's theory). https://en.wikipedia.org/wiki/All_models_are_wrong

Re:Forecasting s-curves is hard by FabHK on Sunday April 19, 2020 @05:32PM (#22918967)
> because of the inherent corruption, greed, biases, and prejudices at play.

You and I must be thinking of different professionals.

At any rate, here are two very very very simple models of this epidemic: a) cases will grow linearly, b) cases will grow exponentially.

Super simple. extremely different outcome. Now, one still has to make policy decisions.

I think the solution is not fewer professionals, but more and better professionals.

Re:Forecasting s-curves is hard by a1369209993 on Sunday April 19, 2020 @06:31PM (#22919341)
> You and I must be thinking of different professionals.

Not sure about you, but I suspect they're thinking of professional politicians and the professionals politicians hire.

Re:Forecasting s-curves is hard by scoot_718 on Sunday April 19, 2020 @07:03PM (#22919529)
> You and I must be thinking of different professionals.

That's the kind of bias he was probably thinking of.

Re:Forecasting s-curves is hard by samatman on Sunday April 19, 2020 @06:20PM (#22919268)
Both of these are wrong, and the exponential one becomes more wrong faster, while being a better match for the beginning of the curve.

Exponential processes don't exist in nature, they always break into some other curve at some point.

Re:Forecasting s-curves is hard by jhayward on Sunday April 19, 2020 @07:39PM (#22919737)
This is a useless bit of pedantry. The exponential portion of the sigmoid curve is the only part that matters to human health, survival, and economic well-being.
Re:Forecasting s-curves is hard by nl on Sunday April 19, 2020 @10:42PM (#22920675)
No it's absolutely not!!

Epidemics are (more) properly modelled by the Gompertz function[1], and the position of the "transition" between the exponential portion and non-exponential points it the important point.

That is exactly what the person you are replying to is saying ("they always break into some other curve at some point.").

[1] https://en.wikipedia.org/wiki/Gompertz_function

Re:Forecasting s-curves is hard by BaronSamedi on Monday April 20, 2020 @07:11AM (#22922843)
Is the Gompertz function the function behind the standard "epi curve"? It appears from the CDC web site and other places that the epi curve is the standard way epidemics are modeled. The CDC even has a simple tutorial for creating them: https://www.cdc.gov/training/quicklearns/createepi/index.htm...
Re:Forecasting s-curves is hard by nl on Monday April 20, 2020 @10:20AM (#22924001)
No.

An epi curve is created from observations and shows new infections per day.

The Gompertz function is a mathematical formula and can be used to estimate total infections up to a date.

However, if you take the epi curve and plot the aggregate number of infections you'll find a curve that the Gompertz function approximates quite well.

Re:Forecasting s-curves is hard by samatman on Sunday April 19, 2020 @08:54PM (#22920168)
Then why, pray tell, is the title of the article we are discussing not "Forecasting exponential curves is hard"?

The entire point is that forecasting exponentials is easy but becomes badly wrong at some point and that point is difficult to forecast

Re:Forecasting s-curves is hard by haneefmubarak on Monday April 20, 2020 @12:07AM (#22921018)
If Einstein's theory roughly says that massive objects deform space proportional to their mass, the effect of which is that massive objects (all else held equal) will tend to move towards each other more so than they would otherwise; meanwhile Newton's theory says that massive objects attract each other proportional to the product of their masses divided by the square of their distance; and Newton's theory does in the vast majority of useful cases yield approximately the same numerical result as Einstein's theory, then how is Newton's theory not an approximation of Einstein's theory?
Re:Forecasting s-curves is hard by ignoramous on Monday April 20, 2020 @07:10AM (#22922840)
Consider the argument from the point of mathematics of it all, and the entire genre of relativity which is a vehement departure from classical physics.

Newton's model captures the essence but isn't the eternal truth. Relativity proved that. Today, singularities have been proven to exist that point to missing pieces in Einstein's theory.

The point is, simpler models are a good approximation even though they don't hold true under scrutiny, so, at what point do we stop obsessing over details and complex models professionals come up with or the policy-makers seek because surely there's law of diminishing returns at play here?

Re:Forecasting s-curves is hard by heavenlyblue on Monday April 20, 2020 @10:01AM (#22923858)
The law of diminishing returns only works in linear spaces. When you reach that point the only progress you can make is to create a better model of reality that would include these wraps.