Adjustments to lie within a circle

  • MHB
  • Thread starter Siron
  • Start date
  • Tags
    Circle
In summary, the conversation discusses how to guarantee that the parameter $\sigma$ is real, which is equivalent to ensuring that the couple $(\mu,\delta)$ lies within a half circle. Two potential approaches are suggested - adjusting $\lambda$ or increasing the radius of the half circle. The speaker also mentions a potential dependency between $\mu$ and $\delta$ on $T$ and suggests exploring that further to potentially find a more fundamental constraint. However, after speaking with their supervisor, adjusting the parameters is deemed not the best solution and they are still discussing alternatives.
  • #1
Siron
150
0
Hello!

In the topic I'm working on, I derived that the parameter $\sigma>0$ satisfies
$$\sigma = \sqrt{\frac{\nu}{T} - \lambda(\mu^2+\delta^2)},$$
where $\nu>0$ denotes the variance and $T>0$ denotes the time. The parameters $\mu \in \mathbb{R}, \delta>0$ and $\lambda>0$ are parameters that I have already computed before $\sigma$ (so I already know their values for different $T$). The problem is: how to guarantee that $\sigma>0$ is real? This can be stated equivalently as:
$$\mu^2+\delta^2 < \frac{\nu}{\lambda T} (*)$$
which means that the couples $(\mu,\delta)$ have to lie within a half circle with radius $\sqrt{\nu}/(\sqrt{\lambda T})$. Now, in most of my computations the derived couples $(\mu,\delta)$ do not satisfy $(*)$. What are some proper mathematical ways to make adjustments such that $(*)$ is satisfied? Obviously I don't want to adjust too many parameters.

Approach 1

My first approach was to find a couple $(\mu^{*},\delta^{*})$ within the half circle such that the distance between the derived couple $(\mu,\delta)$ and $(\mu^{*},\delta^{*})$ is minimal. To that end, I first computed the couple $(\mu',\delta')$ on the half circle, that is, $(\mu')^2+(\delta')^2 = \nu/(\lambda T)$, such that the distance between $(\mu,\delta)$ and $(\mu',\delta')$ is minimal whereafter I adjusted $\delta'$ by $\delta'-\epsilon$ for an arbitrary small $\epsilon>0$ to guarantee that the adjusted couple lies indeed within the half circle. Thus $\mu^{*} = \mu'$ and $\delta^{*} = \delta'-\epsilon$. Disadvantage is that I have to adjust two parameters.

Approach 2
My second thought was to increase the radius of the circle such that the derived couple $(\mu,\delta)$ lies within the half circle. To that end, I will adjust $\lambda>0$ such that $(*)$ is satisfied. Suppose that $(\mu,\delta)$ does not lie within the half circle, that is,
$$\mu^2+\delta^2 > \frac{\nu}{\lambda T},$$
which implies that
$$\lambda > \frac{\nu}{T(\mu^2+\delta^2)}.$$
Hence, replacing $\lambda$ by $\lambda = \nu/(T(\mu^2+\delta^2))-\epsilon$ guarantees that $\sigma$ is real.

NOTE: In the context of my work it's better to not adjust $\nu$ or $T$.

What are some other common approaches?

Many thanks!
 
Physics news on Phys.org
  • #2
It does seem like adjusting $\lambda$ is the easiest way to fix it up. And if that's an acceptable method, I would just go with that!

I do wonder, though, about adjusting $T$. I know you said it's better in your context not to adjust that. However, as $\mu$ and $\delta$ appear to be functions of $T$, I'm curious about the nature of that dependence. Do you have formulae for them? That is, are you able to write down $\mu=\mu(T)$ and $\delta=\delta(T)?$ That might clarify a few things in my mind, at least. In addition, we might actually be able to get at a more fundamental constraint than (*) if we're able to write down these dependencies.
 
  • #3
Thanks for the reply ;)

After a talk with my supervisor it seems that adjusting the parameters $\mu,\delta,\lambda$ is not the best way to go. We still are discussing how we're going to fix it.
 

FAQ: Adjustments to lie within a circle

What is the purpose of adjusting data to lie within a circle?

The purpose of adjusting data to lie within a circle is to create a more accurate representation of the data. In some cases, data may be scattered and not follow a circular pattern, but by adjusting it, we can see the relationships and patterns more clearly.

How do you adjust data to fit within a circle?

To adjust data to fit within a circle, we can use a variety of methods such as scaling, rotation, and translation. These adjustments can be made using mathematical formulas or software tools.

What are the benefits of adjusting data to lie within a circle?

Adjusting data to lie within a circle can help us visualize and analyze the relationships and patterns within the data. It can also make it easier to compare data sets and identify any outliers or anomalies.

Can data always be adjusted to fit within a circle?

No, not all data can be adjusted to fit within a circle. Some data may not have a circular pattern or may be too complex to adjust in a meaningful way. In these cases, other methods of data analysis may be more appropriate.

Are there any limitations to adjusting data to lie within a circle?

Yes, there are some limitations to adjusting data to lie within a circle. It may not always accurately represent the data, and adjustments may introduce errors or distortions. It is important to carefully consider the data and the purpose of the adjustment before making any changes.

Similar threads

Replies
2
Views
525
Replies
3
Views
2K
Replies
3
Views
1K
Replies
2
Views
2K
Replies
22
Views
3K
Replies
1
Views
556
Replies
5
Views
2K
Back
Top