Tagged Questions

1
vote
3answers
89 views

Let $ X_1,X_2,…,X_n$ be i.i.d. $N(\theta_1, \theta_2)$, please prove that $E[(X_1-\theta_1)^4] = 3\theta_2^2$

If $X_{1}$, $X_{2}$, ..., $X_{n}$ is sampled from $N(\theta_1, \theta_2)$, how can I prove that $E [(X_{1} - \theta_1)^{4}] = 3 \theta_2^{2}$? I started off this question finding the completely ...
0
votes
1answer
36 views

Parameter estimation with GMM

I have estimated the parameters of normal distribution with GMM and got the following results: $mean = -0.01168 , p-value = 0.83519, Sd = 1.77 , p-value = 0.00000.$ I'm bit confused in ...
2
votes
1answer
26 views

Multi-dimensional MLE Guassian

I wonder that what is the mu and sigma formula MLE(maximum likelihood estimates) for a 3 dimension guassian ? It is the same form as 1 and 2 dimension (+ 1 mu and sigma for the new vector) ?
0
votes
0answers
58 views

Problem about parameter estimation, recursive representation of posterior distribution.

I am studying in preparation for an exam and got stuck with the following question. The only thing I found out is that maybe I should use a Kalman filter, but no idea how. Given a model $ x = \theta ...
1
vote
0answers
34 views

Sample estimated normal distribution - what will be the expected effect of another sample?

Assume I already have n samples of a 2D variable. I can compute the sample mean and variance. If I assume that the samples are taken from a normal distribution, then using the mean and variance I get ...