Solve Convex Function: Show yf(y^{-1}\textbf{x}) is Convex | Mathmos6

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The discussion focuses on proving the convexity of the function \( yf(y^{-1}\textbf{x}) \) for \( y > 0 \) given that \( f \in C^2(\mathbb{R}) \) is convex. The user, Mathmos6, attempts to derive the necessary conditions using partial derivatives and the Hessian matrix. Key findings include the establishment of the first principal minor and the determinant of the Hessian, which must be non-negative to confirm convexity. The user expresses uncertainty regarding the application of derivatives for the transformed function \( f(x/y, 1) \) and its implications on the convexity proof.

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Homework Statement


How do I show that if [tex]f\in C^2 \text{(}\mathbb{R}\text{)}[/tex] is convex then the function [tex]yf(y^{-1}\textbf{x})[/tex] is convex on (x,y):y>0?

Homework Equations



I know the standard definitions and whatnot about convexity, but I tried chugging through the algebra and didn't have any luck, can anyone show me a nice way to solve this?

Thanks!

-Mathmos6
 
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Mark44 said:
Show us what you tried...

I figured [tex]yf(y^{-1}\textbf{x})=yf(\frac{x}{y},1)[/tex], so set [tex]f_x=\frac{\partial}{\partial{x}}f(\frac{x}{y},1), f_{yy}=\frac{\partial^2}{\partial{y^2}}f(\frac{x}{y},1)[/tex] and so on:

then we get

[tex]\frac{\partial{}}{\partial{x}}(yf(\frac{x}{y},1))=yf_x \Rightarrow \frac{\partial{}^2}{\partial{x^2}}=yf_{xx}[/tex]

and

[tex]\frac{\partial{}^2}{\partial{x}\partial{y}} (yf(\frac{x}{y},1))=f_x+yf_{xy}[/tex]

Also, W.R.T y:

[tex]\frac{\partial{}}{\partial{y}}=yf_y+f(\frac{x}{y},1) \Rightarrow \frac{\partial{}^2}{\partial{y}^2} = yf_{yy}+2f_y[/tex] - right?

Then looking at the Hessian, we know the first principal minor (=yfxx) is >=0 if y is, because f is convex so its corresponding first principal minor must also be >=0. With regards to the second principal minor though, i.e. the determinant of the Hessian, we get

[tex]\frac{\partial{}^2}{\partial{x}^2} \frac{\partial{}^2}{\partial{y}^2} - (\frac{\partial{}^2}{\partial{x}\partial{y}})^2=y^2(f_{xx}f_{yy}-f_{xy}^2)+2y(f_{xx}f_y-f_{xy}f_x)-f_x^2[/tex]

if my algebra is correct. We want to show this >=0 - the first term (the thing in the brackets multiplied by y2) is >=0 because it corresponds to the determinant of the Hessian for f - however, my concern is that I've gone wrong because something in the derivative of f(x/y,1) means this wouldn't work the same as for f(x,y) and so I'm not sure how to proceed... thanks :)
 

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