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 $k rightarrow infty$.
probability probability-theory convergence
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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 $k rightarrow infty$.
probability probability-theory convergence
add a comment |Â
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 $k rightarrow infty$.
probability probability-theory convergence
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 $k rightarrow infty$.
probability probability-theory convergence
edited Jul 26 at 21:06
Daniel Buck
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asked Jul 26 at 20:55
xiorcal
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