The value of E( (||X-μ||-c)^2 )

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Discussion Overview

The discussion revolves around calculating the expected value of the expression E( (||X-μ||-c)^2 ) where X follows a normal distribution N(μ, σ²). Participants explore the implications of this expression and seek methods to derive E(||X-μ||).

Discussion Character

  • Mathematical reasoning
  • Exploratory
  • Homework-related

Main Points Raised

  • One participant asks for the value of E( (||X-μ||-c)^2 ) given that X ~ N(μ, σ²) and provides the context of X and μ as vectors.
  • Another participant expands on the expression by applying the linearity of expectation, suggesting that E( (||X-μ||-c)^2 ) can be broken down into simpler components.
  • A participant expresses uncertainty about finding E(||X-μ||) and refers to a previous question for context.
  • Another participant suggests using the definition of expected value for a function of a random variable and mentions the need to solve Gaussian-type integrals, implying a potential method for finding E(||X-μ||).

Areas of Agreement / Disagreement

The discussion does not reach a consensus on how to compute E(||X-μ||) or the overall expected value expression, with participants presenting different approaches and expressing uncertainty.

Contextual Notes

Participants reference the need for Gaussian-type integrals and the definition of expected value, indicating that certain mathematical steps may be unresolved or require specific assumptions about the distribution.

saintman4
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I would like to ask one more question.

X ~ N (μ, σ2)

If X = [x1 x2] and μ = [μ1 μ2]. What is the value of E( (||X- μ||-c)^2 )?

where c is constant and E(||X- μ||^2)= σ2


Thank ...
 
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[tex]\mathbb{E}[ (||X- \mu||-c)^2 ]=\mathbb{E}[ ||X- \mu||^2-2c||X-\mu||+c^2 ][/tex]

Now [itex]\mathbb{E}[\cdot][/itex] is linear ... does this help?
 
Thank Pere Callahan. But I still don't know how to find E(||X- μ||) as I ask in https://www.physicsforums.com/showthread.php?t=224947

Do you know how to find E(||X- μ||)?

Thank you.
 
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Did yu try to use the definition of the expected value of some function g of a real random Variable X with density function f?
[tex] \mathbb{E}[g(X)]=\int_{\mathbb{R}}{g(x)f(x)dx}[/tex]

You will have to solve some Gaussian-type integrals but it should be straight-forward :smile:
 

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