Jensen inequality, unexplained distribution, very confusing problem

In summary, the conversation discusses the Jensen inequality and its application to a discrete random variable with a given probability mass function. The conversation also mentions the function Y = 1/X and its convexity, and questions whether there may be an issue with the convexity assumption. The conversation ends with a suggestion to research the definition of convexity and further explore the issue.
  • #1
giglamesh
14
0
Hi everyone
I don't know if I can find someone here to help me understand this issue, but I'll try

the jensen inequality can be found here http://en.wikipedia.org/wiki/Jensen%27s_inequality


I have the following discrete random variable [itex]X[/itex] with the following pmf:

x 0 1 2 3
pr(x) 0.110521 0.359341 0.389447 0.140691

and the summation is (1).

defining the function [itex]Y=\frac{1}{X}[/itex]

Then finding the [itex]\bar{X}=\sum_{i=0}^{3}{iPr(i)=1.560308}[/itex]

Now calculating [itex]E[Y]=E[\frac{1}{X}]=\sum_{i=1}^{3}{\frac{1}{i}Pr(i)}=0.6009615[/itex]
then:
[itex]Y(\bar{X})=\frac{1}{\bar{X}}=\frac{1}{1.560308}=0.640899105[/itex]

According to Jensen inequality what should happen:

[itex]E[\frac{1}{X}] \geq \frac{1}{E[X]}[/itex]
but what I got is the opposite case!:cry:

Now also I have to mention the function [itex]Y=\frac{1}{X}[/itex] is convex given that the second derivative is strictly larger than zero.

Do I misunderstand the Jensen inequality? or is there something wrong with the convixity assumption?
Any idea?
 
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  • #2
Without having looked at the details of your calculations, you certaintly have a problem with Y = 1/X for X=0
 
  • #3
Yes you are right to assume it but in the calculation I assumed X>0 when calculating Y.
Even with this assumption I can't approve the opposite inequality.
This can be thought like: choosing one message from X messages problem.

Thanks for reply
 
  • #4
giglamesh said:
Yes you are right to assume it but in the calculation I assumed X>0 when calculating Y.

Well, you cannot simply "remove" X=0 by setting 1/0=0. Then your function is not convex any more, and this is the source of your problem.
 
  • #5
thanks winterfors
But why it's not convex
is there a way to prove that it's concave?
Maybe you mean it's non differentiable at X=0

thanks for reply
 
  • #6
I suggest you look up the definition of a convex/concave function. A function does not have to be differentiable to be convex, for instance is f(x)=abs(x) convex even though is it not differentiable at x=0. Also, that a function is not convex does not imply it is concave, or vice versa.
 
  • #7
I know dear
that's why I asked about why setting Y=0 when X=0 caused the problem
You said the function is not convex any more, here I didn't get it, does it mean now it's concave?
the second derivative is positive since X>0
Anyway thanks for reply I'll do more research on that
 

1. What is Jensen's inequality?

Jensen's inequality is a mathematical concept that states that the expected value of a convex function of a random variable is greater than or equal to the convex function of the expected value of that random variable. In simpler terms, it means that the average of a function is greater than or equal to the function of the average.

2. Why is Jensen's inequality important?

Jensen's inequality has various applications in probability theory, statistics, economics, and engineering. It is used to prove important theorems in these fields and also helps in analyzing and comparing different probability distributions.

3. What is an unexplained distribution?

An unexplained distribution refers to a set of data that cannot be adequately explained by a known probability distribution. This could be due to various factors such as incomplete data, measurement errors, or complex underlying processes.

4. How does Jensen's inequality relate to unexplained distributions?

Jensen's inequality can be used to compare a known probability distribution with an unexplained distribution. If the average of the known distribution is greater than the average of the unexplained distribution, it can be concluded that the unexplained distribution is not a good fit for the data.

5. How can I solve a problem involving Jensen's inequality and unexplained distributions?

Solving such a problem requires a good understanding of probability theory and statistical methods. It also involves careful analysis and interpretation of the data. Seeking help from a statistician or using appropriate statistical software can also be helpful in solving such a problem.

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