A moment inequality
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Let $chi(s)=int_{0}^{1}x(t)^{s}f(t)dt$,
where $x(t)$ and $f(t)$ are real valued continuous functions for
$tin[0,1]$, and $f(t)geq0$.
Is it possible to show that
$left(chi(0)chi(2)-chi(1)^{2}right)left(chi(4)chi(2)-chi(3)^{2}right)-left(chi(3)chi(1)-chi(2)^{2}right)^{2}geq0$
Note: I believe that
$chi(0)chi(2)-chi(1)^{2}geq0$
$chi(4)chi(2)-chi(3)^{2}geq0$
follows from the Cauchy-Schwarz inequality.
(correct me if I am wrong about this).
real-analysis inequalities cauchy-schwarz-inequality
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up vote
3
down vote
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Let $chi(s)=int_{0}^{1}x(t)^{s}f(t)dt$,
where $x(t)$ and $f(t)$ are real valued continuous functions for
$tin[0,1]$, and $f(t)geq0$.
Is it possible to show that
$left(chi(0)chi(2)-chi(1)^{2}right)left(chi(4)chi(2)-chi(3)^{2}right)-left(chi(3)chi(1)-chi(2)^{2}right)^{2}geq0$
Note: I believe that
$chi(0)chi(2)-chi(1)^{2}geq0$
$chi(4)chi(2)-chi(3)^{2}geq0$
follows from the Cauchy-Schwarz inequality.
(correct me if I am wrong about this).
real-analysis inequalities cauchy-schwarz-inequality
Editing to give a more informative title would be useful.
– YCor
Nov 20 at 15:13
add a comment |
up vote
3
down vote
favorite
up vote
3
down vote
favorite
Let $chi(s)=int_{0}^{1}x(t)^{s}f(t)dt$,
where $x(t)$ and $f(t)$ are real valued continuous functions for
$tin[0,1]$, and $f(t)geq0$.
Is it possible to show that
$left(chi(0)chi(2)-chi(1)^{2}right)left(chi(4)chi(2)-chi(3)^{2}right)-left(chi(3)chi(1)-chi(2)^{2}right)^{2}geq0$
Note: I believe that
$chi(0)chi(2)-chi(1)^{2}geq0$
$chi(4)chi(2)-chi(3)^{2}geq0$
follows from the Cauchy-Schwarz inequality.
(correct me if I am wrong about this).
real-analysis inequalities cauchy-schwarz-inequality
Let $chi(s)=int_{0}^{1}x(t)^{s}f(t)dt$,
where $x(t)$ and $f(t)$ are real valued continuous functions for
$tin[0,1]$, and $f(t)geq0$.
Is it possible to show that
$left(chi(0)chi(2)-chi(1)^{2}right)left(chi(4)chi(2)-chi(3)^{2}right)-left(chi(3)chi(1)-chi(2)^{2}right)^{2}geq0$
Note: I believe that
$chi(0)chi(2)-chi(1)^{2}geq0$
$chi(4)chi(2)-chi(3)^{2}geq0$
follows from the Cauchy-Schwarz inequality.
(correct me if I am wrong about this).
real-analysis inequalities cauchy-schwarz-inequality
real-analysis inequalities cauchy-schwarz-inequality
edited Nov 20 at 15:14
Iosif Pinelis
17.1k12157
17.1k12157
asked Nov 20 at 12:59
hopeless
184
184
Editing to give a more informative title would be useful.
– YCor
Nov 20 at 15:13
add a comment |
Editing to give a more informative title would be useful.
– YCor
Nov 20 at 15:13
Editing to give a more informative title would be useful.
– YCor
Nov 20 at 15:13
Editing to give a more informative title would be useful.
– YCor
Nov 20 at 15:13
add a comment |
1 Answer
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6
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This inequality is false in general, by homogeneity considerations. Indeed, it can be rewritten as $L(x)ge R(x)$, where $L(x):=left(chi(0)chi(2)-chi(1)^{2}right)left(chi(4)chi(2)-chi(3)^{2}right)$ and $R(x):=chi(3)chi(1)-chi(2)^{2}$. Take any non-constant positive $x$, so that, by the Cauchy--Schwarz inequality, $R(x)>0$. Then for small enough $t>0$ we have $L(tx)=t^8L(x)<t^4R(x)=R(tx)$.
Added in response to the OP fixing the typo: The inequality is now true. Indeed, let $m_j:=chi(j)$. Without loss of generality, $m_0 m_2-m_1^2>0$, by the Cauchy--Schwarz inequality. The matrix $M:=[m_{i+j}]_{i,j=0}^2$ is positive semidefinite. This follows because
begin{equation}
0leint_0^1Big(sum_{i=0}^2 a_i, x(t)^iBig)^2f(t),dt=sum_{i,j=0}^2 m_{i+j}a_i a_j
end{equation}
for all real $a_0,a_1,a_2$.
So, the determinant of $M$ is $ge0$, which is equivalent to
begin{equation}
m_4ge m_4^*:=frac{m_2^3-2 m_1 m_3 m_2+m_0 m_3^2}{m_0 m_2-m_1^2}.
end{equation}
On the other hand, the difference between the left and right sides of your inequality (with $m_j$ in place of $chi(j)$) is increasing in $m_4$, and the value of this difference is $0$ at $m_4=m_4^*$. Thus, your inequality follows.
Yes, sorry! There should have been a square on the second term. Sorry about this, I have edited the question. Thank you
– hopeless
Nov 20 at 13:28
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
6
down vote
accepted
This inequality is false in general, by homogeneity considerations. Indeed, it can be rewritten as $L(x)ge R(x)$, where $L(x):=left(chi(0)chi(2)-chi(1)^{2}right)left(chi(4)chi(2)-chi(3)^{2}right)$ and $R(x):=chi(3)chi(1)-chi(2)^{2}$. Take any non-constant positive $x$, so that, by the Cauchy--Schwarz inequality, $R(x)>0$. Then for small enough $t>0$ we have $L(tx)=t^8L(x)<t^4R(x)=R(tx)$.
Added in response to the OP fixing the typo: The inequality is now true. Indeed, let $m_j:=chi(j)$. Without loss of generality, $m_0 m_2-m_1^2>0$, by the Cauchy--Schwarz inequality. The matrix $M:=[m_{i+j}]_{i,j=0}^2$ is positive semidefinite. This follows because
begin{equation}
0leint_0^1Big(sum_{i=0}^2 a_i, x(t)^iBig)^2f(t),dt=sum_{i,j=0}^2 m_{i+j}a_i a_j
end{equation}
for all real $a_0,a_1,a_2$.
So, the determinant of $M$ is $ge0$, which is equivalent to
begin{equation}
m_4ge m_4^*:=frac{m_2^3-2 m_1 m_3 m_2+m_0 m_3^2}{m_0 m_2-m_1^2}.
end{equation}
On the other hand, the difference between the left and right sides of your inequality (with $m_j$ in place of $chi(j)$) is increasing in $m_4$, and the value of this difference is $0$ at $m_4=m_4^*$. Thus, your inequality follows.
Yes, sorry! There should have been a square on the second term. Sorry about this, I have edited the question. Thank you
– hopeless
Nov 20 at 13:28
add a comment |
up vote
6
down vote
accepted
This inequality is false in general, by homogeneity considerations. Indeed, it can be rewritten as $L(x)ge R(x)$, where $L(x):=left(chi(0)chi(2)-chi(1)^{2}right)left(chi(4)chi(2)-chi(3)^{2}right)$ and $R(x):=chi(3)chi(1)-chi(2)^{2}$. Take any non-constant positive $x$, so that, by the Cauchy--Schwarz inequality, $R(x)>0$. Then for small enough $t>0$ we have $L(tx)=t^8L(x)<t^4R(x)=R(tx)$.
Added in response to the OP fixing the typo: The inequality is now true. Indeed, let $m_j:=chi(j)$. Without loss of generality, $m_0 m_2-m_1^2>0$, by the Cauchy--Schwarz inequality. The matrix $M:=[m_{i+j}]_{i,j=0}^2$ is positive semidefinite. This follows because
begin{equation}
0leint_0^1Big(sum_{i=0}^2 a_i, x(t)^iBig)^2f(t),dt=sum_{i,j=0}^2 m_{i+j}a_i a_j
end{equation}
for all real $a_0,a_1,a_2$.
So, the determinant of $M$ is $ge0$, which is equivalent to
begin{equation}
m_4ge m_4^*:=frac{m_2^3-2 m_1 m_3 m_2+m_0 m_3^2}{m_0 m_2-m_1^2}.
end{equation}
On the other hand, the difference between the left and right sides of your inequality (with $m_j$ in place of $chi(j)$) is increasing in $m_4$, and the value of this difference is $0$ at $m_4=m_4^*$. Thus, your inequality follows.
Yes, sorry! There should have been a square on the second term. Sorry about this, I have edited the question. Thank you
– hopeless
Nov 20 at 13:28
add a comment |
up vote
6
down vote
accepted
up vote
6
down vote
accepted
This inequality is false in general, by homogeneity considerations. Indeed, it can be rewritten as $L(x)ge R(x)$, where $L(x):=left(chi(0)chi(2)-chi(1)^{2}right)left(chi(4)chi(2)-chi(3)^{2}right)$ and $R(x):=chi(3)chi(1)-chi(2)^{2}$. Take any non-constant positive $x$, so that, by the Cauchy--Schwarz inequality, $R(x)>0$. Then for small enough $t>0$ we have $L(tx)=t^8L(x)<t^4R(x)=R(tx)$.
Added in response to the OP fixing the typo: The inequality is now true. Indeed, let $m_j:=chi(j)$. Without loss of generality, $m_0 m_2-m_1^2>0$, by the Cauchy--Schwarz inequality. The matrix $M:=[m_{i+j}]_{i,j=0}^2$ is positive semidefinite. This follows because
begin{equation}
0leint_0^1Big(sum_{i=0}^2 a_i, x(t)^iBig)^2f(t),dt=sum_{i,j=0}^2 m_{i+j}a_i a_j
end{equation}
for all real $a_0,a_1,a_2$.
So, the determinant of $M$ is $ge0$, which is equivalent to
begin{equation}
m_4ge m_4^*:=frac{m_2^3-2 m_1 m_3 m_2+m_0 m_3^2}{m_0 m_2-m_1^2}.
end{equation}
On the other hand, the difference between the left and right sides of your inequality (with $m_j$ in place of $chi(j)$) is increasing in $m_4$, and the value of this difference is $0$ at $m_4=m_4^*$. Thus, your inequality follows.
This inequality is false in general, by homogeneity considerations. Indeed, it can be rewritten as $L(x)ge R(x)$, where $L(x):=left(chi(0)chi(2)-chi(1)^{2}right)left(chi(4)chi(2)-chi(3)^{2}right)$ and $R(x):=chi(3)chi(1)-chi(2)^{2}$. Take any non-constant positive $x$, so that, by the Cauchy--Schwarz inequality, $R(x)>0$. Then for small enough $t>0$ we have $L(tx)=t^8L(x)<t^4R(x)=R(tx)$.
Added in response to the OP fixing the typo: The inequality is now true. Indeed, let $m_j:=chi(j)$. Without loss of generality, $m_0 m_2-m_1^2>0$, by the Cauchy--Schwarz inequality. The matrix $M:=[m_{i+j}]_{i,j=0}^2$ is positive semidefinite. This follows because
begin{equation}
0leint_0^1Big(sum_{i=0}^2 a_i, x(t)^iBig)^2f(t),dt=sum_{i,j=0}^2 m_{i+j}a_i a_j
end{equation}
for all real $a_0,a_1,a_2$.
So, the determinant of $M$ is $ge0$, which is equivalent to
begin{equation}
m_4ge m_4^*:=frac{m_2^3-2 m_1 m_3 m_2+m_0 m_3^2}{m_0 m_2-m_1^2}.
end{equation}
On the other hand, the difference between the left and right sides of your inequality (with $m_j$ in place of $chi(j)$) is increasing in $m_4$, and the value of this difference is $0$ at $m_4=m_4^*$. Thus, your inequality follows.
edited Nov 20 at 15:12
answered Nov 20 at 13:18
Iosif Pinelis
17.1k12157
17.1k12157
Yes, sorry! There should have been a square on the second term. Sorry about this, I have edited the question. Thank you
– hopeless
Nov 20 at 13:28
add a comment |
Yes, sorry! There should have been a square on the second term. Sorry about this, I have edited the question. Thank you
– hopeless
Nov 20 at 13:28
Yes, sorry! There should have been a square on the second term. Sorry about this, I have edited the question. Thank you
– hopeless
Nov 20 at 13:28
Yes, sorry! There should have been a square on the second term. Sorry about this, I have edited the question. Thank you
– hopeless
Nov 20 at 13:28
add a comment |
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Editing to give a more informative title would be useful.
– YCor
Nov 20 at 15:13