Prove Jensen's Inequality: Convex Functions (a,b) → R

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This discussion focuses on proving Jensen's Inequality for convex functions defined on the interval (a,b) mapping to R. The inequality states that for any convex function f, if x1,...,xn are in (a,b) and c1,...,cn are non-negative weights, then the weighted sum of the function values is greater than or equal to the function value of the weighted average of the inputs. The proof involves induction and the definition of convexity, specifically utilizing the property that for any two points x1 and x2 in (a,b), the inequality holds for a linear combination of these points.

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1. Suppose that f: (a,b) --> R is convex. Prove Jensen's inequality: if x1,...,xn[tex]\in(a,b)[/tex] and c1,...,cn >= 0 s.t. [tex]\sum(c_j)f(x_j)[/tex] >= f([tex]\sum((c_j)(x_j))[/tex]

both summations from j = 1 to n

2: Convex: whenever x1, x2 [tex]\in(a,b)[/tex] and 0 <= c <= 1, we have cf(x1) + (1 + c)f(x2) >= f(cx1 + (1-c)x2)


3. I realize that this is a proof by induction.
I have written the first summation in the form of (cn+1)(xn+1) + (1 - (cn+1)y, and then used my definition of convexity. My issue is trying to figure out what my y is. I know it has something to do with breaking it into a summation from just j=1 to n but I keep going in circles...
 
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Try this:

[tex]\sum_{j=1}^{n+1}c_j x_j = c_{n+1} x_{n+1} + \sum_{j=1}^{n}c_j x_j = c_{n+1} x_{n+1} + \left(\frac{1 - c_{n+1}}{1 - c_{n+1}}\right) \sum_{j=1}^{n}c_j x_j = c_{n+1} x_{n+1} + (1 - c_{n+1}) \sum_{j=1}^{n}\frac{c_j}{1 - c_{n+1}} x_j[/tex]

What is

[tex]\sum_{j=1}^{n}\frac{c_j}{1 - c_{n+1}}[/tex]?
 

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