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0 votes
0 answers
41 views

Unbiased Estimator of Nugget Effect

Question: I am trying the measure the nugget effect, which is parameterized by $(1-\lambda)$ in the following variance-covariance used to describe the multivariate normal distribution of my n-...
A Friendly Fish's user avatar
1 vote
2 answers
94 views

Covariance of Best Linear Unbiased Estimators and arbitrary LUE

I'm working on a problem involving two linear unbiased estimators $T$ and $T'$ of a parameter $\theta$, defined from a sample $\{X_1, \dots, X_n\}$ with mean $\theta$ and finite variance. I aim to ...
Taha Rhaouti's user avatar
4 votes
1 answer
147 views

Why does not this underlying hypergeometric distribution lead to unbiased estimators?

This example is take from Lippman's "Elements of probability and statistics". Let N be the number of fish in a lake the warden wants to estimate. He catches 100 fish, tags them and releases ...
Tryer's user avatar
  • 275
9 votes
1 answer
96 views

Adjusted R2 and bias

Consider the population $R^2$: \begin{equation} \rho^2 = 1- \frac{\sigma^{2}_u}{\sigma^{2}_y} \end{equation} This equation describes the proportion of the variation in $y$ in the population explained ...
Dimitru's user avatar
  • 185
1 vote
0 answers
42 views

Showing that the estimator of the log posterior used in stochastic gradient MCMC is unbiased

In the SGLD paper as well as in this paper it is claimed (paraphrasing) that the following estimator: $$\widetilde{U}(\theta) = -\dfrac{|\mathcal{S}|}{|\widetilde{\mathcal{S}}|} \sum_{{x}\in \...
Tan's user avatar
  • 33
3 votes
1 answer
149 views

Is the sample mean an unbiased estimator of population mean in the presence of autocorrelation?

I've seen previous questions here that the sample mean can be considered an unbiased estimator of the population mean. e.g.1, 2. While the examples seem to refer to independent sample points, it seems ...
JMenezes's user avatar
  • 539
3 votes
1 answer
144 views

Estimating ratio of regression coefficients

What is the best method of estimating a ratio of regression coefficients $\beta_1/\beta_2$ under the usual assumptions / in practice? I have two relatively well approximated signals $X_1, X_2$ and ...
Magemathician's user avatar
3 votes
1 answer
72 views

Tossing Until First Heads Outcome, and Repeating, as a Method for Estimating Probability of Heads

Consider the problem of estimating the heads probability $p$ of a coin by tossing it until the first heads outcome is observed. Say we get $k_1$ tosses, then $U_1 = \frac{1}{k_1}$ is an estimate for $...
Omid Madani's user avatar
4 votes
1 answer
300 views

Cramer-Rao lower bound for the variance of unbiased estimators of $\theta = \frac{\mu}{\sigma}$

Let $X_1, \cdots, X_n$ be a sample from the $N(\mu, \sigma^2)$ density, where $\mu, \sigma^2$ are unknown. I want to find a lower bound $L_n$ which is valid for all sample-sizes $n$ for the variance ...
Oscar24680's user avatar
3 votes
2 answers
560 views

Confusion about the notation in Horvitz-Thompson estimator

I am a bit confused about the terminology used in the context of sampling of populations. The Horvitz-Thompson estimator, as well as the Hansen-Hurwitz estimator, for example, are examples of ...
pompeu's user avatar
  • 33
1 vote
2 answers
51 views

estimator for standard error [closed]

I have searched extensively and I fail to find an answer. If you are not confident, please don't answer or modify the question, since it will confuse readers even more. Agree on some definitions Let $...
SDE_Amazon's user avatar
2 votes
1 answer
87 views

Example when globally unbiased estimator does not exist while locally unbiased estimator exists?

The locally unbiased(l.u.) estimator $\hat{\theta}\left( x \right)$, with $x$ stands for the experiment result, refers to the estimator that satisfies(see Eq(5) of this paper for multiparameter case) $...
narip's user avatar
  • 187
0 votes
1 answer
142 views

Consistent or inconsistent estimator

If $\hat{\theta}_n$ is an estimator for the parameter $\theta$, then the two sufficient conditions to ensure consistency of $\hat{\theta}_n$ are: Bias($\hat{\theta}_n)\to 0$ and Var$(\hat{\theta}_n)\...
user380598's user avatar
1 vote
1 answer
73 views

Can a “reverse unbiased” estimator be created?

Suppose we have a parameter $\theta$ that we want to estimate. We sample an observation (random variable) $X$ from a known distribution $D_{X|\theta}$. Then, we can compute an estimator $\hat\theta(X)$...
Theemathas Chirananthavat's user avatar
1 vote
1 answer
76 views

Is $\sum(x^2 - \bar{x}^2)/(n-1)$ an unbiased estimator of variance?

We know that sample variance $\sum(x- \bar{x})^2/(n-1) = \sum(x^2- 2x\bar{x}+\bar{x}^2)/(n-1)$ is an unbiasedd estimator of variance Is $\sum(x^2 - \bar{x}^2)/(n-1)$ also an unbiased estimator of ...
Zachary HUANG's user avatar

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