Distribution Theory - Uniform Convergence

In summary, we have shown that F is a continuous map from C(O) to D'(O) by using the fact that if a sequence of continuous functions converges to a continuous junction pointwise, then it converges uniformly on any compact.
  • #1
MidnightR
42
0
F: C(Omega) -> D'(Omega); F(f) = F_f

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O = Omega

Introduce the notion of convergence on C(Omega) by

f_p -> f as p -> inf in C(O) if f_p(x) -> f(x) for any xEO

Show that then F is a continuous map from C(O) to D'(O)

Hint: Use that if a sequence of continuous functions converges to a continuous junction pointwise then it converges uniformly on any compact.

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Really not sure :S I'd be really grateful if someone could just get me started so I don't sit here staring at it for hours >.<

I've thought about the definition of continuous functions between topological spaces:

A function F: C(O) → D'(0), where C(0) and D'(0) are topological spaces, is continuous if and only if for every open set V ⊆ D'(O), the inverse image

[itex]F^{-1}(V) = \{x \in C(O) \; | \; F(x) \in V \}[/itex]

is open.

But not sure how to proceed.
 
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  • #2
Answer:We need to show that for any open set V in D'(O) its inverse image F^{-1}(V) is open in C(O). Let V be an open set in D'(O). We know that V can be expressed as a union of sets {f_i} where each f_i is continuous on Omega. By definition, F^{-1}(V) = \{x \in C(O) \; | \; F(x) \in V \}. Since F(x)=F_f and f_i is continuous on Omega, for any x in F^{-1}(V), we know that F(x) is also continuous on Omega. Since each f_i is continuous on Omega, we also know that each x in F^{-1}(V) is continuous on Omega. Now, since we have a sequence of continuous functions converging to a continuous junction pointwise, we can use the fact that this sequence converges uniformly on any compact. This means that for any x in F^{-1}(V), the sequence of functions converging to F(x) does so uniformly on any compact. Since this holds for all x in F^{-1}(V), we can conclude that F^{-1}(V) is open in C(O) and thus F is a continuous map from C(O) to D'(O).
 

What is uniform convergence in distribution theory?

Uniform convergence is a type of convergence in distribution theory where the probability distributions of a sequence of random variables converge uniformly. This means that the difference between the cumulative distribution functions of the random variables becomes smaller and smaller as the number of observations increases.

How is uniform convergence different from other types of convergence in distribution theory?

In uniform convergence, the convergence is uniform across the entire range of possible values for the random variables, rather than just at a specific point or range of values. This makes it a stronger form of convergence.

What is the significance of uniform convergence in distribution theory?

Uniform convergence is important because it ensures that the convergence of a sequence of random variables to a limit is not affected by the specific values of the random variables. This allows for more accurate and stable predictions and estimations in statistical analysis.

How is uniform convergence related to the Central Limit Theorem?

Uniform convergence is a key concept in the proof of the Central Limit Theorem. It ensures that the average of a large number of independent and identically distributed random variables will converge to a normal distribution, regardless of the specific values of the random variables.

Can uniform convergence fail to hold in certain cases?

Yes, uniform convergence can fail to hold if the sequence of random variables is not well-behaved. For example, if the sequence is not independent or identically distributed, uniform convergence may not occur. In these cases, other forms of convergence may still hold.

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