Domain of attraction $F(x)=exp(-x-sin(x))$Computation of $mathbbE[min(U+W,V+W)]$Inverse quantile function for $sin^2(x)$Central limit theorem kind of statement for recordsConvergence of sequence of random variables 2$Z = sum_i=1^T X_i$, $T$ ~ $Geo(p)$, $X_i$ ~ $exp(lambda)$. Then, $Z$ ~ $exp(plambda)$Application of Central Limit Theorem - Uniform DistributionStatistics of Extreme risksExtreme value index of $F(x) = 1-e^ left(-fracx^24right)$What does it mean centering a Gumbel distribution?Maximum Likelihood Estimator for a exp(1/$theta$) distributed rv
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Domain of attraction $F(x)=exp(-x-sin(x))$
Computation of $mathbbE[min(U+W,V+W)]$Inverse quantile function for $sin^2(x)$Central limit theorem kind of statement for recordsConvergence of sequence of random variables 2$Z = sum_i=1^T X_i$, $T$ ~ $Geo(p)$, $X_i$ ~ $exp(lambda)$. Then, $Z$ ~ $exp(plambda)$Application of Central Limit Theorem - Uniform DistributionStatistics of Extreme risksExtreme value index of $F(x) = 1-e^ left(-fracx^24right)$What does it mean centering a Gumbel distribution?Maximum Likelihood Estimator for a exp(1/$theta$) distributed rv
$begingroup$
I need to show that $F(x)=exp(-x-sin(x)),x >0$ is in no domain of attraction. That means that there exist no $a_k >0, b_k in mathbbR, k in mathbbN$ with $limlimits_k to infty fracU(kx)-b(k)a(k)=D(x)$ where $D(x)=G^leftarrow(e^frac1x),$ $G$ is a nondegenerate distribution function and $U=(frac11-F)^leftarrow$.
As a hint i know that the following holds $$ limlimits_k to infty U(n_kx)-log(n_k)= U_1(x)$$
where $U_1$ is the inverse of $exp(x+sin(x))$ and $n_k=[exp(2pi k)].$
Any approach?
probability-distributions stochastic-analysis extreme-value-theorem
$endgroup$
add a comment |
$begingroup$
I need to show that $F(x)=exp(-x-sin(x)),x >0$ is in no domain of attraction. That means that there exist no $a_k >0, b_k in mathbbR, k in mathbbN$ with $limlimits_k to infty fracU(kx)-b(k)a(k)=D(x)$ where $D(x)=G^leftarrow(e^frac1x),$ $G$ is a nondegenerate distribution function and $U=(frac11-F)^leftarrow$.
As a hint i know that the following holds $$ limlimits_k to infty U(n_kx)-log(n_k)= U_1(x)$$
where $U_1$ is the inverse of $exp(x+sin(x))$ and $n_k=[exp(2pi k)].$
Any approach?
probability-distributions stochastic-analysis extreme-value-theorem
$endgroup$
add a comment |
$begingroup$
I need to show that $F(x)=exp(-x-sin(x)),x >0$ is in no domain of attraction. That means that there exist no $a_k >0, b_k in mathbbR, k in mathbbN$ with $limlimits_k to infty fracU(kx)-b(k)a(k)=D(x)$ where $D(x)=G^leftarrow(e^frac1x),$ $G$ is a nondegenerate distribution function and $U=(frac11-F)^leftarrow$.
As a hint i know that the following holds $$ limlimits_k to infty U(n_kx)-log(n_k)= U_1(x)$$
where $U_1$ is the inverse of $exp(x+sin(x))$ and $n_k=[exp(2pi k)].$
Any approach?
probability-distributions stochastic-analysis extreme-value-theorem
$endgroup$
I need to show that $F(x)=exp(-x-sin(x)),x >0$ is in no domain of attraction. That means that there exist no $a_k >0, b_k in mathbbR, k in mathbbN$ with $limlimits_k to infty fracU(kx)-b(k)a(k)=D(x)$ where $D(x)=G^leftarrow(e^frac1x),$ $G$ is a nondegenerate distribution function and $U=(frac11-F)^leftarrow$.
As a hint i know that the following holds $$ limlimits_k to infty U(n_kx)-log(n_k)= U_1(x)$$
where $U_1$ is the inverse of $exp(x+sin(x))$ and $n_k=[exp(2pi k)].$
Any approach?
probability-distributions stochastic-analysis extreme-value-theorem
probability-distributions stochastic-analysis extreme-value-theorem
asked Mar 13 at 7:34
John DoeJohn Doe
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