Finding the PDF of Z = arctan(x) from a Gaussian Distribution

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SUMMARY

The discussion focuses on deriving the probability density function (pdf) of Z = arctan(X) where X follows a Gaussian distribution defined by f_{X}(x) = (1/σ√(2π)) exp(-x²/(2σ²)). The transformation Z = g(X) is one-to-one when restricted to the interval Z ∈ (-π/2, π/2). The resulting pdf f_Z(z) is expressed as f_Z(z) = (sec²(z)) f_X(x), which simplifies to f_Z(z) = (1 + tan²(z)) (1/σ√(2π)) exp(-tan²(z)/(2σ²)). The final step involves verifying that this pdf integrates to one over the specified bounds.

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Homework Statement



If X is represented by the Gaussian distribution, that is,

f_{X}(x) = \frac{1}{\sigma\sqrt{2\pi}} \exp{(-\frac{x^2}{2\sigma^2})}

find an expression for the pdf fZ(z) of Z = arctan(x).

The Attempt at a Solution



If Z =g(X), then g(X) is multivalued unless the range of the function is restricted to Z \in \left(-\frac{\pi}{2}, \frac{\pi}{2}\right)

Under this condition, the function is one to one, and so the probability that z will be in some interval (z, z + dz) is equal to the probability that x will be in the corresponding interval (x, x + dx). In other words,

|f_Z(z) dz| = |f_X(x) dx|

f_Z(z) = \left| \frac{dx}{dz} \right| f_X(x)

= \frac{d}{dz} (\tan z) f_X(x)

= (\sec^2(z)) f_X(x)

= (1+\tan^2(z)) \frac{1}{\sigma\sqrt{2\pi}} \exp{(-\frac{\tan^2(z)}{2\sigma^2})}​

Am I doing this right?
 
Last edited:
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I don't see a problem; but you'll need to verify that it integrates to one between the bounds.
 

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