Sum of 2 Non-identical Uniforms RVs?

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In summary, the probability distribution of Z, where Z = X+Y and X and Y are independently distributed uniform random variables with ranges (0,1) and (-9,0) respectively, can be found using characteristic functions. The characteristic function of Z is given by the product of the characteristic functions of X and Y, and the pdf can be obtained by performing an inverse Fourier transform. For the specific example of two non-identically distributed uniform variables, the result is expected to be the combination of the two separate uniform distributions with the area normalized to 1.
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zli034
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Does anyone know to formulate the pmf and pdf of sum 2 uniform random variables of non-identically distributed?

Say rv X is uniformly distributed range (0,1), and rv Y is uniformly distribute range (-9,0).
For Z = X+Y, what is the probability distribution of Z?

Thanks in advance. So many things are just nice to know.
 
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For independently distributed random variables [itex]x_i[/itex], the distribution of a sum of these variables,

[tex]z = a_1x_1 + \dots a_N x_N[/tex]

can be found using characteristic functions. The characteristic function of a random variable is given by

[tex]\varphi_{X_k}(t) = \langle \exp(ix_k t)\rangle[/tex]
i.e., the expectation value of exp(ix_k t). Note that this is just a Fourier transform for continuous variables and a Fourier series for discrete variables, so the original pdf can be recovered by performing an inverse Fourier transform.

Given this, the characteristic funtion of z is

[tex]\varphi_Z(t) = \prod_{k=1}^N \varphi_{X_k}(a_kt)[/tex]

So, to get the pdf of z, inverse Fourier transform the resulting expression.

Try applying this to your specific case of two different uniform variables. (I'm not sure off the top of my head if the inverse FT can be performed in closed form. It will involve the product of two sinc functions. Intuitively, though, I would expect the result for the specific example to be the two separate uniform distributions stitched together and the area renormalized to 1, since the ranges do not overlap)
 

What does "Sum of 2 Non-identical Uniforms RVs" refer to?

"Sum of 2 Non-identical Uniforms RVs" refers to a mathematical operation that combines two random variables (RVs) that follow a uniform distribution. It is often used in statistics and probability calculations.

What is a uniform distribution?

A uniform distribution is a probability distribution where all possible outcomes have equal likelihood of occurring. This means that the data is evenly spread out across the range of possible values.

How do you calculate the sum of 2 non-identical uniform RVs?

To calculate the sum of 2 non-identical uniform RVs, you can use the following formula: Sum = a + b, where a and b are the two RVs. This assumes that the two RVs have the same range of possible values.

What is the expected value of the sum of 2 non-identical uniform RVs?

The expected value of the sum of 2 non-identical uniform RVs is equal to the sum of the expected values of the individual RVs. In other words, it is the average of all possible outcomes of the sum.

Why is the sum of 2 non-identical uniform RVs important in scientific research?

The sum of 2 non-identical uniform RVs is important in scientific research because it allows for the analysis and prediction of data that follows a uniform distribution. This can be useful in various fields such as economics, physics, and engineering.

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