What Function Produces a Smooth Curve with Specific Symmetry and Decay?

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Discussion Overview

The discussion revolves around identifying a mathematical function that produces a smooth curve with specific characteristics: starting at (0,0), having a maximum at a specified point n, and approaching zero as x approaches infinity. The participants explore various functions and their properties, including symmetry and decay, within the context of fictional physics.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant suggests that the curve should be symmetrical about n logarithmically, although this is not confirmed.
  • Another participant proposes the lognormal probability density function (pdf) as a candidate, noting it meets the criteria and has adjustable parameters ##\mu## and ##\sigma## to modify its shape.
  • A different function, ##x^n e^{-cx}##, is introduced, which also meets the criteria, with the maximum occurring at ##x=n/c##.
  • There is a discussion about the relationship between parameters, with one participant clarifying that the peak of the function depends on the ratio of n to c.
  • One participant mentions the possibility of using GeoGebra to visualize the functions and their parameters.
  • Another participant questions the relationship between n, ##\mu##, and ##\sigma##, suggesting a different formulation for n in the context of the lognormal distribution.
  • There is a humorous exchange where one participant asserts that the drawn curve resembles a Poisson distribution, which is contested by another participant.

Areas of Agreement / Disagreement

Participants express multiple competing views regarding the appropriate function to model the desired curve. There is no consensus on a single function or the exact relationships between the parameters.

Contextual Notes

Participants discuss various mathematical forms and their implications, but there are unresolved assumptions about the definitions and relationships between parameters, particularly in the context of the lognormal distribution.

DaveC426913
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TL;DR
Is there a simple function that would produce a curve in this family?
Helping someone with some fictional physics.

He's looking for a function that will produce a curve similar to this (poor geometry is my doing, assume smooth curvature):
1630359239267.png

Starts at 0,0.
Maximum at n.
Reaches zero at infinity.
The cusp is not sharp, it's a curve (which, I think suggests at least two variables?).

Presumably, the curve is symmetrical about n logarithmically, but not a given.
 
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The lognormal pdf curve matches the four criteria listed, as do a number of other right-skewed, long-tailed probability distributions (could try pareto, weibull).

It has two parameters ##\mu,\sigma## that can be adjusted to modify the shape.

To make the maximum (mode of the distribution) happen at ##x=n## we set a constraint:

$$n=\mu-\sigma^2$$
 
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andrewkirk said:
The lognormal pdf curve matches the four criteria listed, as do a number of other right-skewed, long-tailed probability distributions (could try pareto, weibull).

It has two parameters that can be adjusted to modify the shape.
Heh. I literally just stumbled upon this before tabbing back here.
 
##x^n e^{-cx}##
It starts at 0,0, it has a maximum at x=n/c, it goes to zero for x to infinity.

If the logarithmic property is required, ##e^{-\log(x/n)^2}## will do the job (it's just a normal distribution adjusted using log(x)), but it's a bit more complicated.
 
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mfb said:
##x^n e^{-cx}##
It starts at 0,0, it has a maximum at x=n/c, it goes to zero for x to infinity.

If the logarithmic property is required, ##e^{-\log(x/n)^2}## will do the job (it's just a normal distribution adjusted using log(x)), but it's a bit more complicated.
Thanks. What is c?

Also,where can I plug this into see it?
 
DaveC426913 said:
Thanks. What is c?
You should start with the fact that you want the peak to be at n. THIS IS NOT NECESSARILY THE n IN NBF'S POST. Using ##y= x^m e^{-cx}##, the peak is at ##m/c=n## (your ##n##). So you have a new function, ##y= x^{nc} e^{-cx}## with only the parameter, ##c##.
DaveC426913 said:
Also,where can I plug this into see it?
I like the free download of GeoGebra. It is easy to type in an equation and get a plot. In this case, you would want to first set up a parameter, c, and set the integer, n, to a value. Then define the function ##y= x^{nc} e^{-cx}##.
Here is an example.
1630391481588.png
 
Last edited:
DaveC426913 said:
Thanks. What is c?
An adjustable parameter. The ratio n/c is the position of the peak.

Example plots, both with their peak at x=1. I multiplied the second example by 3 for better comparison.
 
Here is a GeoGebra example of the lognormal method. Suppose you want the maximum value to be at n=2. That is the ##mean## of the lognormal distribution. So ##mean=2##. The lognormal has two parameters: ##NormMean## and ##NormVariance##. You can set the ##NormVariance \gt 0## parameter as you wish. The smaller you make it, the higher the maximum at n=2. The value of ##NormMean## is calculated as ##NormMean = ln(mode)+NormVariance^2##. With these parameters set, the lognormal PDF is determined. Here is the GeoGebra example.
1630425031073.png
 
andrewkirk said:
To make the maximum (mode of the distribution) happen at ##x=n## we set a constraint:

$$n=\mu-\sigma^2$$
I think that should be ##n=e^{\mu-\sigma^2}##
 
  • #10
Thanks all.
 
  • #11
What you have drawn looks like a Poisson distribution to me ...
 
  • #12
Svein said:
What you have drawn looks like a Poisson distribution to me ...
No.

This, sir, is a Poisson Distribution:
1630532463267.png


*for clarity that's a moustache, beret and ascot on a cod.
 
Last edited:

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