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Convergence generally means that a sequence of a certain sample quantity approaches a constant as the sample size tends to infinity. Convergence is also a property of an iterative algorithm to stabilize on some aim value.

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Convergence Issues for Bootstrap Distributions

By assumption, for each $i=1,\dots , k$ we can find a value of the of the index that parametrizes the convergence in probability (which is implicit in your statement, and that I will refer to "the sample … By the assumption of convergence in probability (as the sample size increases), if the sample size sufficiently large: \begin{align*} & P( |\hat{F}^*(a_i) - F(a_i) | \ge \epsilon ) \le \frac{\delta}{k} …
VictorZurkowski's user avatar
3 votes

Extreme Value Theory - Show: Normal to Gumbel

Here is a "direct" approach. Let $a_n > 0$, $b_n$ to be determined so that $a_nx+b_n \rightarrow +\infty$ for all $x$. From L'Hospital's rule, $$ \underset{A \rightarrow \infty }{lim} \frac{\int_A^{+ …
VictorZurkowski's user avatar