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

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The discussion centers on the conditions necessary for the approximation Prob(wx + y < c) ≈ Prob(wx < c) as w approaches infinity. It is suggested that the expected values E(x) and E(y) should be finite, with E(y) being significantly smaller than E(x). As w increases, the probability density functions are analyzed to demonstrate that the limits lead to equivalent probabilities. The integration of the probability density functions confirms that both expressions converge to the same result. Ultimately, the conditions for the approximation hold true under these specified expectations.
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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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