A question on continuity of probability functions

In summary, the conversation discusses Saeed Ghahramani's proof of the continuity of the probability function in his book "Fundamentals of Probability." The conversation touches on the use of the classic theorem of calculus and its application to a set function. The definition of continuity is also mentioned, as well as the difference between increasing and decreasing sequences and convergent sequences. There is a request for clarification on the use of R and the definition of a theorem. Finally, the importance of convergent sequences is emphasized in the proof.
  • #1
Mathelogician
35
0
Hi everybody! In Saeed Ghahramani's "fundamentals of probability" he proves the continuity of the probability function f:P(S) ->[0,1] as follows:

He Defines the notions of increasing and decreasing sequences of sets (here sets of events) and then defines infinite limits of such sequences (as infinite union and infinite intersection of the sets of events; respectively) and then he claims proving the continuity of f using a way the following classic theorem of calculus:
f : R -> R is continuous on R if and only if, for every convergent sequence {xn} n =1 to infinite in R, limf({xn})=f(lim{xn}) as n goes to infinity.
But
1-the classic theorem is for functions from R to R; how can he use it for a set function (which is from a collection of sets to R, here)
2- Even if he is right, he only proves the continuity of the cases of increasing and decreasing sequences; not convergent(which he has not defined!) in general.

Now what to do with this problem?!
Regards.
 
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  • #2
Let me know if i am not clear enough!
Regards.
 
  • #3
Speaking for myself, I have difficulty responding.
Your text looks more like statements than like questions.
Furthermore, I did not read your book and your statements are not clear enough for me.
It also seems like you are using math words not entirely correctly, making it difficult to understand your problem.

Let's take a look at some of your words.
You mention the classic theorem of calculus.
I know of no such thing, but reading on, it seems you meant the definition of continuity.
Did you?

Then you mention a set function (being a function on a collection of sets), but I do not understand which function you mean.
Can you clarify?

It may be that I can figure out what you mean if I look long enough and try to understand long enough.
But to be honest, I don't feel like spending that time.

Perhaps you can state your questions more like questions and with clear references?
 
  • #4
Here you can find all the story:

Regards.
 
  • #5
There does not seem to be a reference to a classic theorem of calculus.
But there is a reference to how continuity is defined according to calculus.

I don't see a function that is defined on a collection of sets.

What is your question exactly?
 
  • #6
OK! as i mentioned at first, by classic i meant the same theorem of continuity (using convergent sequences)
The probability function IS defined on the collection of sets of events P(S) [Indeed the power set of the set S of sample space!] see line 8 in first page!

But the theorem of calculus is:
1- For functions from R to R .[Not any set like P(S) to R]
2- Used for convergent sequences [Not increasing or decreasing sequences!]

Now is that clear?!
 
  • #7
Mathelogician said:
OK! as i mentioned at first, by classic i meant the same theorem of continuity (using convergent sequences)
The probability function IS defined on the collection of sets of events P(S) [Indeed the power set of the set S of sample space!] see line 8 in first page!

But the theorem of calculus is:
1- For functions from R to R .[Not any set like P(S) to R]
2- Used for convergent sequences [Not increasing or decreasing sequences!]

Now is that clear?!

I'll continue with asking for clarifications if you don't mind.
Usually it helps if we can get all symbols and definitions clear.

You mention R as opposed to R.
What do you mean by R? Is it different from the set of real numbers?

On an off note, a theorem is the same as a proposition, a lemma, a corollary, identity, rule, law, or principle.
They all follow from a given set of axioms (or postulates), but mathematically there is no clear distinction between them.
A theorem is different from an axiom or postulate.
It is also different from a definition.
If I understand you correctly, you're not talking about a theorem of continuity, but about its definition. See for instance here.

As for convergent sequences, there is no reason why an increasing or decreasing sequence wouldn't be convergent.
For instance 1/x is a decreasing sequence that converges to zero.
It is just an attribute of a convergent sequence whether it is increasing, decreasing, alternating, or something else.
 
  • #8
R is the set of real numbers!

The theorem that i mentioned is can also be used as an equivalent definition of continuity![ If you want to ask what is the meaning of "equivalent", the i suggest you a first course in mathematical logic!] [[And the other definition of continuity is the one concluded by the equation(for continuity of f in the point a) Lim f(x) = f(a) as x->a ; and the epsilon-delta definition of limitation - and again if you don't know the epsilon-delta definition of limits, you are invited to review a first course on Calculus!]]

And about the convergence: convergence is not equivalent to increasing/decreasing. So if we are supposed to prove something about convergent sequences, we are not allowed to prove it for increasing/decreasing sequences![Or if so, we got to mention that it's for increasing/decreasing convergent sequences; and then we have to prove the assertion for non-increasing/non-decreasing cases!]

---------------
I think here in this topic, we have logic problem more than math!
 
  • #9
Mathelogician said:
R is the set of real numbers!

The theorem that i mentioned is can also be used as an equivalent definition of continuity![ If you want to ask what is the meaning of "equivalent", the i suggest you a first course in mathematical logic!] [[And the other definition of continuity is the one concluded by the equation(for continuity of f in the point a) Lim f(x) = f(a) as x->a ; and the epsilon-delta definition of limitation - and again if you don't know the epsilon-delta definition of limits, you are invited to review a first course on Calculus!]]

And about the convergence: convergence is not equivalent to increasing/decreasing. So if we are supposed to prove something about convergent sequences, we are not allowed to prove it for increasing/decreasing sequences![Or if so, we got to mention that it's for increasing/decreasing convergent sequences; and then we have to prove the assertion for non-increasing/non-decreasing cases!]

---------------
I think here in this topic, we have logic problem more than math!

Your statements are correct, although your tone appears to be a bit disrespectful.
You do realize that this forum consists of volunteers?

I still don't understand your usage of R as opposed to R.
Nor do I understand which function on a collection of sets you intended.
And you seem to have misinterpreted my statement about convergence.

Anyway, it appears you have no questions.
 
  • #10
ILikeSerena said:
Anyway, it appears you have no questions.

Well said.

This thread is only heading to worse places so I'm going to close it.
 

Related to A question on continuity of probability functions

1. What is the definition of continuity in probability functions?

Continuity in probability functions refers to the smoothness and unbrokenness of the function's graph. In other words, it means that there are no sudden jumps or breaks in the probability values as the input variable changes.

2. How do we determine if a probability function is continuous?

A probability function is considered continuous if it satisfies three conditions: 1) The function's domain must be a connected interval, 2) The function must be defined for all values within the interval, and 3) The limit of the function as the input variable approaches a specific value within the interval must exist and be equal to the function's value at that point.

3. What is the significance of continuity in probability functions?

Continuity in probability functions is essential because it ensures that the function accurately represents the relationship between the input variable and the probability values. It also allows us to make precise predictions and calculations using the function.

4. Can a probability function be both continuous and discontinuous?

No, a probability function cannot be both continuous and discontinuous. A function can only be either continuous or discontinuous, but not both, at any given point in its domain.

5. What are some common examples of continuous probability functions?

Some common examples of continuous probability functions include the normal distribution, exponential distribution, and beta distribution. These functions are widely used in various fields such as statistics, finance, and engineering to model and analyze data.

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