Moment generating function is finite given limsup propertyConvergence properties of a moment generating function for a random variable without a finite upper bound.Finding the Moment Generating Function given f(x)Express moment generating function as sum of two othersProbability: Deriving The Moment Generating Function Given the Definition of a Continuous Random Variablelinear transformation of factorial moment generating functionmixture distribution moment generating functionIdentifying random variables from moment generating functions and using characteristic functionsMoment generating function within another functionmoment-generating function is well definedExpectation property of moment generating function
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Moment generating function is finite given limsup property
Convergence properties of a moment generating function for a random variable without a finite upper bound.Finding the Moment Generating Function given f(x)Express moment generating function as sum of two othersProbability: Deriving The Moment Generating Function Given the Definition of a Continuous Random Variablelinear transformation of factorial moment generating functionmixture distribution moment generating functionIdentifying random variables from moment generating functions and using characteristic functionsMoment generating function within another functionmoment-generating function is well definedExpectation property of moment generating function
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For a random variable $X$ define the moment-generating function $M_X(t) = mathbbE[e^tX]$. If it is known that
$$limsup_xtoinftyfraclogmathbbP(X>x)x =- c < 0,$$
how can it be shown that $M_X(t) < infty$ for all $t in [0, c)$? (source, Ex. 2)
probability probability-theory random-variables limsup-and-liminf moment-generating-functions
$endgroup$
add a comment |
$begingroup$
For a random variable $X$ define the moment-generating function $M_X(t) = mathbbE[e^tX]$. If it is known that
$$limsup_xtoinftyfraclogmathbbP(X>x)x =- c < 0,$$
how can it be shown that $M_X(t) < infty$ for all $t in [0, c)$? (source, Ex. 2)
probability probability-theory random-variables limsup-and-liminf moment-generating-functions
$endgroup$
add a comment |
$begingroup$
For a random variable $X$ define the moment-generating function $M_X(t) = mathbbE[e^tX]$. If it is known that
$$limsup_xtoinftyfraclogmathbbP(X>x)x =- c < 0,$$
how can it be shown that $M_X(t) < infty$ for all $t in [0, c)$? (source, Ex. 2)
probability probability-theory random-variables limsup-and-liminf moment-generating-functions
$endgroup$
For a random variable $X$ define the moment-generating function $M_X(t) = mathbbE[e^tX]$. If it is known that
$$limsup_xtoinftyfraclogmathbbP(X>x)x =- c < 0,$$
how can it be shown that $M_X(t) < infty$ for all $t in [0, c)$? (source, Ex. 2)
probability probability-theory random-variables limsup-and-liminf moment-generating-functions
probability probability-theory random-variables limsup-and-liminf moment-generating-functions
asked Oct 30 '18 at 22:37
jIIjII
1,22021327
1,22021327
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1 Answer
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$begingroup$
$Ee^tX =int_0^infty Pe^tX >x, dx$. It is enough to show that $int_M^infty Pe^tX >x, dx <infty$ for some $M$. Let $t<c$ and $epsilon <c-t$. By hypothesis there exists $x_0$ such that $log PX>x <x( -c+epsilon)$ for $x > x_0$. Hence $PX>x <e^x(-c+epsilon)$ and $int_M^infty Pe^tX >x, dx =int_M^infty PX >(log , x) /tdx<int_M^infty x^frac -c+epsilon t dx<infty$ because $(-c+epsilon) /t <-1$.
$endgroup$
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1 Answer
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1 Answer
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$begingroup$
$Ee^tX =int_0^infty Pe^tX >x, dx$. It is enough to show that $int_M^infty Pe^tX >x, dx <infty$ for some $M$. Let $t<c$ and $epsilon <c-t$. By hypothesis there exists $x_0$ such that $log PX>x <x( -c+epsilon)$ for $x > x_0$. Hence $PX>x <e^x(-c+epsilon)$ and $int_M^infty Pe^tX >x, dx =int_M^infty PX >(log , x) /tdx<int_M^infty x^frac -c+epsilon t dx<infty$ because $(-c+epsilon) /t <-1$.
$endgroup$
add a comment |
$begingroup$
$Ee^tX =int_0^infty Pe^tX >x, dx$. It is enough to show that $int_M^infty Pe^tX >x, dx <infty$ for some $M$. Let $t<c$ and $epsilon <c-t$. By hypothesis there exists $x_0$ such that $log PX>x <x( -c+epsilon)$ for $x > x_0$. Hence $PX>x <e^x(-c+epsilon)$ and $int_M^infty Pe^tX >x, dx =int_M^infty PX >(log , x) /tdx<int_M^infty x^frac -c+epsilon t dx<infty$ because $(-c+epsilon) /t <-1$.
$endgroup$
add a comment |
$begingroup$
$Ee^tX =int_0^infty Pe^tX >x, dx$. It is enough to show that $int_M^infty Pe^tX >x, dx <infty$ for some $M$. Let $t<c$ and $epsilon <c-t$. By hypothesis there exists $x_0$ such that $log PX>x <x( -c+epsilon)$ for $x > x_0$. Hence $PX>x <e^x(-c+epsilon)$ and $int_M^infty Pe^tX >x, dx =int_M^infty PX >(log , x) /tdx<int_M^infty x^frac -c+epsilon t dx<infty$ because $(-c+epsilon) /t <-1$.
$endgroup$
$Ee^tX =int_0^infty Pe^tX >x, dx$. It is enough to show that $int_M^infty Pe^tX >x, dx <infty$ for some $M$. Let $t<c$ and $epsilon <c-t$. By hypothesis there exists $x_0$ such that $log PX>x <x( -c+epsilon)$ for $x > x_0$. Hence $PX>x <e^x(-c+epsilon)$ and $int_M^infty Pe^tX >x, dx =int_M^infty PX >(log , x) /tdx<int_M^infty x^frac -c+epsilon t dx<infty$ because $(-c+epsilon) /t <-1$.
answered Oct 31 '18 at 0:10
Kavi Rama MurthyKavi Rama Murthy
71.7k53170
71.7k53170
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