What Are the Conditions for Prob(wx + y < c) ≈ Prob(wx < c) as w → ∞?

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The discussion focuses on the conditions required for the approximation Prob(wx + y < c) ≈ Prob(wx < c) as w approaches infinity. Key insights include the necessity for the expected values E(x) and E(y) to be finite, with E(y) needing to be significantly smaller than E(x). The probability density functions f(x), f(y), and f(x,y) are utilized to derive the equivalence of the two probabilities in the limit, confirming that they converge to the same integral representation.

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Given two random variables x and y, and a constant c

What conditions are needed to make:

Prob( w x + y &lt; c ) \approx Prob( w x &lt; c ), \text{ for } w \rightarrow \infty

Can anyone help? I think E(x) &lt; \infty and E(y) &lt; \infty might do. Is this right?

tks!
 
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I think you need the expected value of y an order of magnitude less than E(x).
 
In the limit as w \rightarrow \infty I believe they are always equal. I will use the probability density functions (f(x),f(y), and f(x,y)) to give my reasoning.

P(wx &lt; c) = P(x &lt; c/w) = P(x &lt; 0) in the limit of w \rightarrow \infty
= \int_{-\infty}^{0}f(x)dx = \int_{-\infty}^{0}\int_{-\infty}^{\infty}f(x,y)dydx

To calculate the probability you have to add up the region of the density for which wx+y < c, which can be achieved by integrating for each x from y=-infinity to the line y=-wx+c:

P(wx +y &lt; c) = \int_{-\infty}^{\infty}\int_{-\infty}^{-wx+c}f(x,y)dydx

In the limit this becomes the y-axis, so we actually have in this case:
= \int_{-\infty}^{0}\int_{-\infty}^{\infty}f(x,y)dydx = \int_{-\infty}^{0}f(x)dx

and so they are equivalent.
 

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