Question

UMVUE of $\theta$ when $X_1,\ldots,X_n$ are i.i.d with pdf $f(x)=\frac{(\ln\theta)\theta^x }{\theta -1}$

score 159 · Answer 1 · 2019-01-22 16:13:46

159

Views

UMVUE of $\theta$ when $X_1,\ldots,X_n$ are i.i.d with pdf $f(x)=\frac{(\ln\theta)\theta^x }{\theta -1}$

Published on 22 Jan 2019 - 16:13

score 4k · Answer 2 · 2019-01-25 09:44:07

4k

Views

$X_i$ follows Bernoulli distribution find UMVUE of $\theta(1-\theta)$

Published on 25 Jan 2019 - 9:44

score 235 · Answer 3 · 2019-01-25 23:16:56

235

Views

Diverging Integral with Bessel Function

Published on 25 Jan 2019 - 23:16

score 153 · Answer 4 · 2026-03-25 11:16:01

153

Views

Determine the value of $α$ for which the $MSE(T)$ is minimal.

Published on 25 Mar 2026 - 11:16

score 217 · Answer 5 · 2026-02-23 13:00:30

217

Views

confidence interval with MLE estimator

Published on 23 Feb 2026 - 13:00

score 354 · Answer 6 · 2019-01-27 10:05:04

354

Views

Method of moments estimator for $\theta^2$ when $X_i\sim p_{\theta}(x)=\frac{2x}{\theta^2}1_{0{\leq}x{\leq}\theta}$

Published on 27 Jan 2019 - 10:05

score 155 · Answer 7 · 2019-01-27 20:43:06

155

Views

Testing certain estimators for consistency

Published on 27 Jan 2019 - 20:43

score 155 · Answer 8 · 2019-01-29 02:50:14

155

Views

Find the UMVUE of $b^{\mu}$

Published on 29 Jan 2019 - 2:50

score 38 · Answer 9 · 2019-01-30 13:02:08

38

Views

Estimating a parameter from a sequence of signals with non i.i.d. noise

Published on 30 Jan 2019 - 13:02

score 1.3k · Answer 10 · 2026-03-25 18:04:38

1.3k

Views

What is the maximum likelihood of a binomial distribution?

Published on 25 Mar 2026 - 18:04

score 258 · Answer 11 · 2026-03-25 17:32:45

258

Views

What is an intuitive application of estimators?

Published on 25 Mar 2026 - 17:32

score 51 · Answer 12 · 2019-02-03 20:01:39

51

Views

Based on the ideas of Parameter Estimation and Fitting Probability Distributions, what stops us from making any function be a PDF(PMF)?

Published on 03 Feb 2019 - 20:01

score 19 · Answer 13 · 2019-02-05 15:45:46

19

Views

Examples where estimating the derivative is easier than estimating the actual quantity.

Published on 05 Feb 2019 - 15:45

score 63 · Answer 14 · 2019-02-06 08:39:02

63

Views

Regression Unbiased Estimator

Published on 06 Feb 2019 - 8:39

score 71 · Answer 15 · 2019-02-06 12:16:56

71

Views

Let $X_1,X_2...X_n $ be a random sample from a $N(\theta ,\theta^2 )$ distribution, where $\theta >0$ is unknown.

Published on 06 Feb 2019 - 12:16

List Question

UMVUE of $\theta$ when $X_1,\ldots,X_n$ are i.i.d with pdf $f(x)=\frac{(\ln\theta)\theta^x }{\theta -1}$

$X_i$ follows Bernoulli distribution find UMVUE of $\theta(1-\theta)$

Diverging Integral with Bessel Function

Determine the value of $α$ for which the $MSE(T)$ is minimal.

confidence interval with MLE estimator

Method of moments estimator for $\theta^2$ when $X_i\sim p_{\theta}(x)=\frac{2x}{\theta^2}1_{0{\leq}x{\leq}\theta}$

Testing certain estimators for consistency

Find the UMVUE of $b^{\mu}$

Estimating a parameter from a sequence of signals with non i.i.d. noise

What is the maximum likelihood of a binomial distribution?

What is an intuitive application of estimators?

Based on the ideas of Parameter Estimation and Fitting Probability Distributions, what stops us from making any function be a PDF(PMF)?

Examples where estimating the derivative is easier than estimating the actual quantity.

Regression Unbiased Estimator

Let $X_1,X_2...X_n $ be a random sample from a $N(\theta ,\theta^2 )$ distribution, where $\theta >0$ is unknown.

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