Characteristic function of a Gaussian

In summary, we need to find the characteristic function of the Gaussian distribution, which is given by the function P(x) in the provided link. The characteristic function can be written as a definite integral involving the function f_X(x) and the variable k. A hint is provided, but it needs to be corrected as the "-a" term in the square root should be positive, not negative. By applying the definition of the characteristic function and making a substitution, we can simplify the integral and use the corrected hint to obtain the characteristic function in terms of k and the mean \langle x \rangle and standard deviation \sigma .
  • #1
fluidistic
Gold Member
3,924
261

Homework Statement


I must find the characteristic function of the Gaussian distribution [itex]f_X(x)=\frac{1}{\sqrt{2\pi}\sigma} e^{-\frac{1}{2} \left [ \frac{(x- \langle x \rangle )^2}{\sigma ^2} \right ]}[/itex]. If you cannot see well the latex, it's the function P(x) in http://mathworld.wolfram.com/NormalDistribution.html.

Homework Equations


The characteristic function is [itex]\phi _X(k)=\int _{-\infty}^{\infty} e^{ikx}f_X(x)dx[/itex].
And a hint given (it seems I didn't copy it well): [itex]\int _{-\infty}^{\infty} e^{-ax^2+bx}dx = \sqrt {\frac{\pi}{-a}} e^{-\frac{b^2}{4a}}[/itex]. The -a in the square root bothers me, maybe I got it wrong but Wolfram Alpha isn't helping me either.

The Attempt at a Solution


I applied the definition of the characteristic function and reached [itex]\phi _X(k)=\frac{1}{\sqrt{2\pi} \sigma} \int _{-\infty}^{\infty} \frac{e^{ikx}}{e^{\frac{1}{2} \left [ \frac{(x-\langle x \rangle )^2}{\sigma ^2} \right ] }}dx[/itex].
I define [itex]z=\frac{x-\langle x \rangle }{\sigma }[/itex] which pushes me to [itex]\phi _X(k)=\frac{e^{ik\langle x \rangle}}{\sqrt{2\pi}} \int _{-\infty}^{\infty}e^{ikz\sigma}-\frac{z^2}{2}dz[/itex]. It is the form I could in principle apply the hint given. But as it is here, "a" would be 1/2 and the "-a" in the square root would make no sense... or would if I consider complex numbers?!
Considering complex numbers (I think it's fair since the characteristic function must be complex for the moments to be defined), I reach that [itex]\phi _X(k)=ie^{ik \langle x \rangle +8k^2 \sigma ^2}[/itex].
I'd appreciate extremely very much if someone could check my result and correct me if I'm wrong. Thank you.

Edit: I used the wolfram integrator, the correct evaluation is [itex]\int _{-\infty}^{\infty} e^{-ax^2+bx}dx = \sqrt {\frac{\pi}{a}} e^{\frac{b^2}{4a}}[/itex] giving me [itex]\phi _X(k)=e^{ik \langle x \rangle - \frac{k^2 \sigma ^2}{2}}[/itex]. I think it is a correct result.
 
Last edited:
Physics news on Phys.org
  • #2
fluidistic said:

Homework Statement


I must find the characteristic function of the Gaussian distribution [itex]f_X(x)=\frac{1}{\sqrt{2\pi}\sigma} e^{-\frac{1}{2} \left [ \frac{(x- \langle x \rangle )^2}{\sigma ^2} \right ]}[/itex]. If you cannot see well the latex, it's the function P(x) in http://mathworld.wolfram.com/NormalDistribution.html.


Homework Equations


The characteristic function is [itex]\phi _X(k)=\int _{-\infty}^{\infty} e^{ikx}f_X(x)dx[/itex].
And a hint given (it seems I didn't copy it well): [itex]\int _{-\infty}^{\infty} e^{-ax^2+bx}dx = \sqrt {\frac{\pi}{-a}} e^{-\frac{b^2}{4a}}[/itex]. The -a in the square root bothers me, maybe I got it wrong but Wolfram Alpha isn't helping me either.


The Attempt at a Solution


I applied the definition of the characteristic function and reached [itex]\phi _X(k)=\frac{1}{\sqrt{2\pi} \sigma} \int _{-\infty}^{\infty} \frac{e^{ikx}}{e^{\frac{1}{2} \left [ \frac{(x-\langle x \rangle )^2}{\sigma ^2} \right ] }}dx[/itex].
I define [itex]z=\frac{x-\langle x \rangle }{\sigma }[/itex] which pushes me to [itex]\phi _X(k)=\frac{e^{ik\langle x \rangle}}{\sqrt{2\pi}} \int _{-\infty}^{\infty}e^{ikz\sigma}-\frac{z^2}{2}dz[/itex]. It is the form I could in principle apply the hint given. But as it is here, "a" would be 1/2 and the "-a" in the square root would make no sense... or would if I consider complex numbers?!
Considering complex numbers (I think it's fair since the characteristic function must be complex for the moments to be defined), I reach that [itex]\phi _X(k)=ie^{ik \langle x \rangle +8k^2 \sigma ^2}[/itex].
I'd appreciate extremely very much if someone could check my result and correct me if I'm wrong. Thank you.

Edit: I used the wolfram integrator, the correct evaluation is [itex]\int _{-\infty}^{\infty} e^{-ax^2+bx}dx = \sqrt {\frac{\pi}{a}} e^{\frac{b^2}{4a}}[/itex] giving me [itex]\phi _X(k)=e^{ik \langle x \rangle - \frac{k^2 \sigma ^2}{2}}[/itex]. I think it is a correct result.

If ##X \sim \text{N}(\mu,\sigma^2)## then we can write ##X = \mu + \sigma Z,## where ##Z \sim \text{N}(0,1).## So, if ##\tilde{\phi}(w)## is the characteristic function of the unit normal Z, then the characteristic function of X is
[tex]\tilde{\phi}_X(k) = E \,e^{i k (\mu + \sigma Z)}
= e^{i k \mu} \tilde{\phi}(\sigma k).[/tex]

RGV
 
  • #3
Hey Ray!
Ray Vickson said:
If ##X \sim \text{N}(\mu,\sigma^2)## then we can write ##X = \mu + \sigma Z,## where ##Z \sim \text{N}(0,1).## So, if ##\tilde{\phi}(w)## is the characteristic function of the unit normal Z, then the characteristic function of X is
[tex]\tilde{\phi}_X(k) = E \,e^{i k (\mu + \sigma Z)}
= e^{i k \mu} \tilde{\phi}(\sigma k).[/tex]

RGV
Ok this mean what I've done has chances to be right if I understand well; your [itex]\mu[/itex] is my [itex]\langle x \rangle[/itex].
I get the correct first 2 raw moments, which is a good sign.
 

Related to Characteristic function of a Gaussian

1. What is a Gaussian distribution?

A Gaussian distribution, also known as a normal distribution, is a type of probability distribution that is commonly used to model continuous random variables. It is characterized by its bell-shaped curve and is symmetric around its mean.

2. What is the characteristic function of a Gaussian?

The characteristic function of a Gaussian is a mathematical function that fully describes the distribution of a Gaussian random variable. It is defined as the expected value of the complex exponential of the random variable.

3. How is the characteristic function of a Gaussian used in statistics?

The characteristic function of a Gaussian is used to calculate the moments and other properties of a Gaussian distribution. It can also be used to derive the probability density function and the cumulative distribution function of a Gaussian distribution.

4. Can the characteristic function of a Gaussian be used to describe any type of data?

No, the characteristic function of a Gaussian is specific to Gaussian distributions and cannot be used to describe other types of distributions. However, it is a very commonly used distribution in statistics due to its many desirable properties.

5. How does the shape of a Gaussian distribution affect its characteristic function?

The shape of a Gaussian distribution does not affect its characteristic function. The characteristic function is solely determined by the mean and standard deviation of the distribution, not its shape.

Similar threads

  • Calculus and Beyond Homework Help
Replies
2
Views
425
  • Calculus and Beyond Homework Help
Replies
3
Views
1K
  • Calculus and Beyond Homework Help
Replies
2
Views
994
  • Calculus and Beyond Homework Help
Replies
13
Views
543
  • Calculus and Beyond Homework Help
Replies
3
Views
479
  • Calculus and Beyond Homework Help
Replies
4
Views
286
Replies
5
Views
1K
  • Calculus and Beyond Homework Help
Replies
7
Views
963
  • Calculus and Beyond Homework Help
Replies
1
Views
490
  • Calculus and Beyond Homework Help
Replies
1
Views
393
Back
Top