Convergence in distribution of rv order

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I'm trying to understand how a certain convergence-in-distribution result follows:



Let $u_1,dotsc,u_k$ be uniformly distributed random variables on $[0,1]$ and let $v$ be a random variable also defined on $[0,1]$ with distribution function $F_v$.



The probability that $v$ is ranked $i$, with $i=0,dotsc,k$, with rank $0$ when $v > max(u_1,dotsc, u_k)$, is given by:



$$R_i,k = kchoose iint_0^1t^i(1-t)^k-i textdF_v(t) $$



Now, let $X^(k)$ be a sequence of random variables taking values $frac0k, frac1k, dotsc, frackk$ with probabilities $R_0,k$, $R_1,k,dotsc,R_k,k$.



The sequence $X^(k)$ converges in distribution to $F_v$ as $k rightarrow infty$.







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    I'm trying to understand how a certain convergence-in-distribution result follows:



    Let $u_1,dotsc,u_k$ be uniformly distributed random variables on $[0,1]$ and let $v$ be a random variable also defined on $[0,1]$ with distribution function $F_v$.



    The probability that $v$ is ranked $i$, with $i=0,dotsc,k$, with rank $0$ when $v > max(u_1,dotsc, u_k)$, is given by:



    $$R_i,k = kchoose iint_0^1t^i(1-t)^k-i textdF_v(t) $$



    Now, let $X^(k)$ be a sequence of random variables taking values $frac0k, frac1k, dotsc, frackk$ with probabilities $R_0,k$, $R_1,k,dotsc,R_k,k$.



    The sequence $X^(k)$ converges in distribution to $F_v$ as $k rightarrow infty$.







    share|cite|improve this question























      up vote
      -1
      down vote

      favorite









      up vote
      -1
      down vote

      favorite











      I'm trying to understand how a certain convergence-in-distribution result follows:



      Let $u_1,dotsc,u_k$ be uniformly distributed random variables on $[0,1]$ and let $v$ be a random variable also defined on $[0,1]$ with distribution function $F_v$.



      The probability that $v$ is ranked $i$, with $i=0,dotsc,k$, with rank $0$ when $v > max(u_1,dotsc, u_k)$, is given by:



      $$R_i,k = kchoose iint_0^1t^i(1-t)^k-i textdF_v(t) $$



      Now, let $X^(k)$ be a sequence of random variables taking values $frac0k, frac1k, dotsc, frackk$ with probabilities $R_0,k$, $R_1,k,dotsc,R_k,k$.



      The sequence $X^(k)$ converges in distribution to $F_v$ as $k rightarrow infty$.







      share|cite|improve this question













      I'm trying to understand how a certain convergence-in-distribution result follows:



      Let $u_1,dotsc,u_k$ be uniformly distributed random variables on $[0,1]$ and let $v$ be a random variable also defined on $[0,1]$ with distribution function $F_v$.



      The probability that $v$ is ranked $i$, with $i=0,dotsc,k$, with rank $0$ when $v > max(u_1,dotsc, u_k)$, is given by:



      $$R_i,k = kchoose iint_0^1t^i(1-t)^k-i textdF_v(t) $$



      Now, let $X^(k)$ be a sequence of random variables taking values $frac0k, frac1k, dotsc, frackk$ with probabilities $R_0,k$, $R_1,k,dotsc,R_k,k$.



      The sequence $X^(k)$ converges in distribution to $F_v$ as $k rightarrow infty$.









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      share|cite|improve this question




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      edited Jul 26 at 21:06









      Daniel Buck

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      asked Jul 26 at 20:55









      xiorcal

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