Chi or Rayleigh or Ricean?

In summary, the conversation discusses the problem of determining the distribution of Z, which is a linear combination of two normal distributions X and Y. For Z to have a certain distribution (Chi, Rayleigh, or Ricean), the means and variances of X and Y must meet certain criteria. However, in the case being discussed, the means and variances do not meet these criteria, making it challenging to determine the distribution of Z. The conversation also mentions the use of numerical methods to manage the distribution of a linear combination of non-central chi squared random variables, but notes that finding an analytic distribution may be difficult. Lastly, there is a question about how Z is derived in the error analysis.
  • #1
ay0034
11
0
Hello all,

I've been working on error analysis of the system, and I finally faced a big problem.

Let X~N(mu1, sigma1^2) and Y~N(mu2, sigma2^2), and Z=sqrt( X^2 + Y^2 )


For Z to be a Chi, mu's should be zero and sigma's should be 1, to be a Rayleigh, mu's should be zero and two sigma's should be the same, and finally to be a Ricean, mu's can be different from each other, but two sigma's should be the same.

Yes, that's all I know. But in my case, mu's are different and sigma's are different as well. In this case, what is 'Z'?

I appreciated it in advance.
 
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  • #2
Plz help!
 
  • #3
It's a non-central chi distribution.
 
  • #4
For a non-central chi distribution, means can be different. But can variances be different as well? As far as I know, variances must be 1.
 
  • #5
Err, sorry, got a bit over-enthusiastic and thought it should fit nicely, but seems it doesn't after all, so yes looks more complicated.
 
  • #6
And don't think you'll get a nice analytic distribution for this. There seem to be a few numerical methods out there for managing the distribution of a linear combination of non-central chi squared random variables though, which is fairly close to what you want (apart from the square root)
 
  • #7
thank you so much. I'll look it up.
 
  • #8
How is the Z derived in the error analysis?
 

What is Chi distribution?

The Chi distribution is a continuous probability distribution that is used to model the sum of squares of randomly-distributed variables. It is also known as the squared normal distribution and is commonly used in statistical tests and confidence intervals.

What is Rayleigh distribution?

The Rayleigh distribution is a continuous probability distribution that is used to model the magnitude of a vector whose components are independent and identically distributed. It is commonly used in signal processing and communication systems to model the amplitude of a signal in the presence of noise.

What is Ricean distribution?

The Ricean distribution, also known as the Rician distribution, is a continuous probability distribution that is used to model the amplitude of a signal in the presence of both line-of-sight and scattered components. It is commonly used in wireless communication systems to model the received signal strength.

What is the relationship between Chi and Rayleigh distributions?

The Rayleigh distribution is a special case of the Chi distribution, where the degrees of freedom parameter is equal to 2. This means that the Rayleigh distribution can be obtained by squaring a Chi-distributed random variable. In other words, the Rayleigh distribution is a specific case of the Chi distribution when it is restricted to positive values only.

How are Chi, Rayleigh, and Ricean distributions used in practice?

These distributions are commonly used in various fields, such as signal processing, wireless communication, and statistics. They are used to model and analyze various types of data, such as signal amplitudes, noise levels, and sum of squares of random variables. They are also used in hypothesis testing and parameter estimation in statistical analysis.

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