Convergence in measure

A mode of convergence where the set of large errors has measure tending to zero.
Convergence in measure

A convergence in measure is the following notion of convergence for a (fn)(f_n) of on a (X,A,μ)(X,\mathcal{A},\mu): we say that fnf_n converges in measure to a measurable function ff if for every ε>0\varepsilon>0,

μ({xX: fn(x)f(x)>ε})0as n. \mu\big(\{x\in X:\ |f_n(x)-f(x)|>\varepsilon\}\big)\to 0 \quad\text{as }n\to\infty.

This definition treats two functions as close whenever they differ by more than ε\varepsilon only on a set of small measure. If μ(X)<\mu(X)<\infty, then implies convergence in measure, but the converse can fail.

Examples:

  • On ([0,1],B,λ)([0,1],\mathcal{B},\lambda) with λ\lambda, the functions fn=1[0,1/n]f_n=\mathbf{1}_{[0,1/n]} satisfy fn0f_n\to 0 in measure because λ({fn>1/2})=λ([0,1/n])=1/n0\lambda(\{|f_n|>1/2\})=\lambda([0,1/n])=1/n\to 0.
  • On (R,B,λ)(\mathbb{R},\mathcal{B},\lambda), the functions fn=1[n,n+1]f_n=\mathbf{1}_{[n,n+1]} do not converge in measure to 00 because for ε=12\varepsilon=\tfrac12 one has λ({fn>ε})=λ([n,n+1])=1\lambda(\{|f_n|>\varepsilon\})=\lambda([n,n+1])=1 for all nn.