Exactly, That is the idea.
The induction is trivial. The difficult step is proving the non-trivial base case, n=2, which is awfully tedious.Well, I think that question was relatively easy for this forum so I decided to share a slightly more challenging induction question:
prove for every positive integer n, if
for all i = 1,..,n
then
where
n=2 is true by Minkowski's Inequality (for Sums)Well, I think that question was relatively easy for this forum so I decided to share a slightly more challenging induction question:
prove for every positive integer n, if
for all i = 1,..,n
then
where
To be honest that was how I solved it initially but when I tried to solve it without using that inequality, at extension2 level, I also had to go through a not pleasant algebraic manipulation. Just to confirm for n=2 did you multiply the inequality byn=2 is true by Minkowski's Inequality (for Sums)
The specified case is p=-1, which is applicable since all variables involved are strictly positive.
I didn't even attempt it lolTo be honest that was how I solved it initially but when I tried to solve it without using that inequality, at extension2 level, I also had to go through a not pleasant algebraic manipulation. Just to confirm for n=2 did you multiply the inequality by ?
haha, fair enough. I think if you try that, it's not that bad.I didn't even attempt it lol
That's a nice method. Jensen's inequality is powerful, it's a shame we don't learn it in 4unitI didn't even attempt it lol
BUT
I have a method.
Jensen's Inequality in 2 variables.
The function f(x,y) → 1/(1/x + 1/y) is convex in x and y, so:
(f(a₁,b₁) + f(a₂,b₂))/2 ≤ f((a₁+a₂)/2,(b₁+b₂)/2)
Multiply both sides by 2 to achieve the desired result.
did you evaluate the Hessian matrix at a particular point? Otherwise I don't know how you got det hessian matrix = 0As an added aside, the hessian matrix for the function is zero, so it has no determined convexity.
But the first partial derivatives are strictly negative, so the function is strictly decreasing along the individual axes.
Monotone and decreasing, with limiting slope towards zero, this should be sufficient for convexity. (Unsure if it technically follows)
The hessian matrix is zero anywhere the function is defined. Check it yourself, it's not that bad.did you evaluate the Hessian matrix at a particular point? Otherwise I don't know how you got det hessian matrix = 0
Also about having negative first partial derivative in each direction, I haven't done any calculation to check whether is negative or not but I take your word for it. That does not imply the function is monotone or decreasing in every direction moreover the way the function is defined, the boundaries (x,0) and (0,y) are undefined unless you force the function at those boundaries to be zero.
Yes you're right I checked the matrix and the determinant is indeed zero. I do agree the function is decreasing in each axis but I think the first partial in each direction is strictly positive.The hessian matrix is zero anywhere the function is defined. Check it yourself, it's not that bad.
as for the technical matter, the function is positive for positive inputs, and monotone decreasing by the first derivatives (maybe now would be a good time to start learning vectors lmao) along each respective direction (but not overall decreasing), with interesting behaviour when x and y are very close in magnitude.
Well that doesn't prevent convexity, which is the desired property...Yes you're right I checked the matrix and the determinant is indeed zero. I do agree the function is decreasing in each axis but I think the first partial in each direction is strictly positive.
If f is convex, the inequality should be the other way round.I didn't even attempt it lol
BUT
I have a method.
Jensen's Inequality in 2 variables.
The function f(x,y) → 1/(1/x + 1/y) is convex in x and y, so:
(f(a₁,b₁) + f(a₂,b₂))/2 ≤ f((a₁+a₂)/2,(b₁+b₂)/2)
Multiply both sides by 2 to achieve the desired result.
Yes, I already realised that mistake...It is easy to show that function f(x,y) = (xy)/(x+y) (x, y > 0) is not convex (e.g. along the line y = 1, the function is x/(x+1) (x > 0), which is not convex).
To get the inequality direction you wrote, we'd want f(x,y) to be concave, so you should try investigating concavity rather convexity, if you want to try that method.