What is the Construction of R using Equivalence Classes of Cauchy Sequences?

In summary, the proof presented relates to the construction of R using equivalence classes of Cauchy sequences. It states that for any a in R, there exists a sequence b in Q such that the limit of b is x. This is proven by showing that for any b in the equivalence class of Cauchy sequences that converge to x, there exists an r in Q+ and n in N such that for all n greater than N, the absolute value of b_n minus x is less than r. This implies that the limit of b is indeed x. The process of proving this is similar to the standard delta-epsilon proof for Cauchy sequences.
  • #1
autre
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This proof I think is related to our construction of R in class using equivalences classes of Cauchy sequences:

Let a[itex]\in[/itex]R, then there exists a sequence b s.t. {b_n}[itex]\in[/itex]Q for all n[itex]\in[/itex]N and lim {b_n} = x.

Here's my attempt:

Let [{b_n}][itex]\in[/itex]R be the equivalence class of all Cauchy sequences that converge to x. Thus, [{b_n}] = x. Let {b_n}[itex]\in[/itex][{b_n}]. Then, [itex]\exists[/itex]r[itex]\in[/itex]Q+ and n[itex]\in[/itex]N s.t. [itex]\forall[/itex]n>N, |b_n -x|<r. Thus, lim {b_n} = x.

I feel like I'm missing something, as if I missed a step somewhere. Ideas?
 
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  • #2
autre said:
This proof I think is related to our construction of R in class using equivalences classes of Cauchy sequences:

Let a[itex]\in[/itex]R, then there exists a sequence b s.t. {b_n}[itex]\in[/itex]Q for all n[itex]\in[/itex]N and lim {b_n} = x.

Here's my attempt:

Let [{b_n}][itex]\in[/itex]R be the equivalence class of all Cauchy sequences that converge to x. Thus, [{b_n}] = x. Let {b_n}[itex]\in[/itex][{b_n}]. Then, [itex]\exists[/itex]r[itex]\in[/itex]Q+ and n[itex]\in[/itex]N s.t. [itex]\forall[/itex]n>N, |b_n -x|<r. Thus, lim {b_n} = x.

I feel like I'm missing something, as if I missed a step somewhere. Ideas?

Hello autre.

Since you are talking about Cauchy sequences, all the convergence theorems automatically are implied (they can be proven for a general Cauchy sequence).

Maybe what you could do is look at the actual proof that all Cauchy sequences converge in the delta-epsilon setting.

Unfortunately the proof that I have is from material I took in a Wavelets course and I can not distribute the content freely, but I'm sure there has to be some analysis book out there that does your standard delta-epsilon proof for these sequences, and based on that you could either use it directly, or use the proof to suggest a valid epsilon for your problem.

I'm sorry I can't be more specific at this time, but again if the sequence is a valid Cauchy sequence, then there really should not be more to do.

Hopefully someone more well versed than myself can give you more specific advice (and correct me if I am wrong).
 
  • #3
How are you defining such things as "[itex]a- x[/itex]" (a rational) and "|x|" for x an equivalence class of Cauchy sequences?
 
  • #4
How are you defining such things as "a−x" (a rational) and "|x|" for x an equivalence class of Cauchy sequences?

Good question. That didn't really make sense. Maybe I should have:

Let {b_n}∈[{b_n}] and {a_n}}∈x. Then, ∃r∈Q+ and n∈N s.t. ∀n>N, |b_n -a_n|<r. Thus, lim {b_n} = x.

Would that work?
 

1. What is the purpose of the "Construction of R" question?

The "Construction of R" question refers to the process of building a statistical model in the R programming language. It is used to analyze and interpret data in a variety of research fields.

2. How is the "Construction of R" question different from other statistical methods?

The "Construction of R" question is different from other statistical methods in that it specifically uses the R programming language to create and analyze models. This allows for more advanced and customizable analyses compared to other methods.

3. What are the steps involved in the "Construction of R" process?

The steps involved in the "Construction of R" process depend on the specific model being built, but generally include data preparation, model selection, model fitting, and model evaluation. These steps may also involve data visualization and statistical testing.

4. What are the benefits of using R for the "Construction of R" question?

Using R for the "Construction of R" question has several benefits, including its open-source nature, wide range of statistical packages, and ability to handle large datasets. It also allows for reproducible research, as the code used for the analysis can be shared and replicated by others.

5. Are there any limitations to using R for the "Construction of R" question?

While R has many advantages for statistical modeling, it also has some limitations. These include a steep learning curve for beginners, potential errors in code, and limited technical support. However, there is a large and active online community of R users who can offer assistance and guidance.

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