Skip to main content

All Questions

5 questions with no upvoted or accepted answers
1 vote
1 answer
34 views

Why can we get better asymptotic global estimators even for IID random variables?

Let $X_1,...,X_N$ be IID random variables sampled from a parametrised distribution $p_\theta$, and suppose my goal is to retrieve $\theta$ from these samples. We know that the MLE provides an ...
glS's user avatar
  • 383
1 vote
0 answers
157 views

Is this the only way to determine if a parameter can be estimated efficiently?

I am tasked with determining if a particular parameter can be estimated efficiently. Given that an efficient estimator is an unbiased estimator which achieves the Cramer-Rao lower-bound, is the only ...
David's user avatar
  • 1,276
1 vote
0 answers
105 views

Fisher information $J_y(\theta)$ for transformation $y=F(x)$

Consider a multivariate random variable $x$ with density function $P_x(\theta)$ for a scalar parameter $\theta$. Assume the Fisher information $J_x(\theta)$ is known. Now, for a transformation (...
Uri Cohen's user avatar
  • 437
0 votes
0 answers
286 views

Fisher matrix for a discrete distribution

Let $\mathbf{X} = \{X_1, \ldots, X_n\}$ be a sample of i.i.d. variables following a discrete distribution with parameters $\mathbf{p}^T = (p_1, p_2, p_3)$. How can I find the Fisher information matrix ...
GingerBadger's user avatar
0 votes
0 answers
1k views

Proof Sample Variance is Minimum Variance Unbiased Estimator for Unknown Mean

I am trying to prove that the unbiased sample variance is a minimum variance estimator. In this problem I have a Normal distribution with unknown mean (and the variance is the parameter to estimate so ...
Susy A.'s user avatar