2013Unpublished venueRequires access

Convergence Types. Almost Sure Convergence. L p ‐Convergence. Convergence in Probability

Ionuţ Florescu, Ciprian A. Tudor

Open publisher page 0 citations

Abstract

The convergence of sequences of random variables to some limit random variable is an important concept in probability theory, and it is a very important application to statistics and stochastic processes. In this chapter, the authors will talk about a notion of convergence defined purely by the distribution of random variables. Before they introduce notions taking advantage of the structure of the probability space, they would like to recall the more traditional real analysis types of convergence. In real analysis there is a notion of convergence which is applicable to probability theory. That concept is looking at the convergence of integrals of functions instead of the convergence of the functions. They have seen that convergence almost sure (a.s.) and convergence in Lp are generally not compatible. However, they will give an integrability condition that will make all the convergence types equivalent.

About this research paper

What this paper is about

The convergence of sequences of random variables to some limit random variable is an important concept in probability theory, and it is a very important application to statistics and stochastic processes. In this chapter, the authors will talk about a notion of convergence defined purely by the distribution of random variables. Before they introduce notions taking advantage of the structure of the probability space, they would like to recall the more traditional real analysis types of convergence. In real analysis there is a notion of convergence which is applicable to probability theory. That concept is looking at the convergence of integrals of functions instead of the convergence of the functions. They have seen that convergence almost sure (a.s.) and convergence in Lp are generally not compatible. However, they will give an integrability condition that will make all the convergence types equivalent.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The convergence of sequences of random variables to some limit random variable is an important concept in probability theory, and it is a very important application to statistics and stochastic processes. In this chapter, the authors will talk about a notion of convergence defined purely by the distribution of random variables. Before they introduce notions taking advantage of the structure of the probability space, they would like to recall the more traditional real analysis types of convergence. In real analysis there is a notion of convergence which is applicable to probability theory. That concept is looking at the convergence of integrals of functions instead of the convergence of the functions. They have seen that convergence almost sure (a.s.) and convergence in Lp are generally not compatible. However, they will give an integrability condition that will make all the convergence types equivalent.

Key concepts: Convergence of random variables, Compact convergence, Modes of convergence (annotated index), Normal convergence, Convergence tests, Convergence (economics), Dominated convergence theorem, Weak convergence

Related papers

Back to paper searchBrowse research topicsOriginal source
Convergence Types. Almost Sure Convergence. L p ‐Convergence. Convergence in Probability — Research Paper | ScholarLens