Convergence concepts in probability MOC

Empirical cumulative distribution function

Given a random sample {𝑋𝑗}𝑛𝑗=1 of independent and identically distributed real random variables with CDF 𝐹, let 𝑅𝑛(π‘₯) count how many of {𝑋𝑗}𝑛𝑗=1 are less than or equal to π‘₯; i.e.

𝑅𝑛(π‘₯)=π‘›βˆ‘π‘—=11{𝑋𝑗≀π‘₯}

implying 𝑅𝑛(π‘₯) ∼Bin⁑(𝑛,𝐹(π‘₯)). The empirical cumulative distribution function of {𝑋𝑗}𝑛𝑗=1 is prob

𝐹𝑛(π‘₯)=1𝑛𝑅𝑛(π‘₯)=π‘›βˆ‘π‘—=11{𝑋𝑗≀π‘₯}

and 𝐹𝑛(π‘₯) converges almost surely to 𝐹(π‘₯) as 𝑛 β†’βˆž, hence it is an estimator of the true CDF.


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