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Regarding samples gotten from MCMC

In Bayesian, in my view, the MCMC is a procedure to draw samples from your priors (your assumptions) and follow your hierarchical model (also your assumptions), you can estimate the posterior ...
Jinchen Zeng's user avatar
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Regarding samples gotten from MCMC

The sampling algorithms are designed in such a way that frequency of samples is proportional to probability associated with respective state of parameter space. Then, if you for example want to ...
NeuroPanda's user avatar
1 vote

How to sample (without replacement) from a large set by randomly sampling non-overlapping subsets?

You have to know $N,$ even if finding out requires examining all the videos. Then you can make a second pass to sample them. But you can sample them separately, one video at a time. Suppose the ...
whuber's user avatar
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Posterior Distribution in a Bayesian Multivariate Normal Model

If I understand you correctly, the only distributions depending on $\sigma^2_{\mathbf{b}}$ are the prior distributions of $\sigma^2_{\mathbf{b}}$ and $\tilde{\mathbf{b}} \mathrel{:=} \mathrm{vec}(\...
statmerkur's user avatar
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Why do Denoising Diffusion Probabilistic Models (DDPM) add noise according to $\sigma_t$ during sampling?

I was also confused and let me just try to chime in. So here are 2 ways I like to think about it. 1): Intuitively, since the model is deterministic, and it is supposed to undo the forward diffusion ...
jyan1999's user avatar
6 votes
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Sampling the max among $N$ samples from the Rayleigh distribution

To quote from Wikipedia The probability density function of the Rayleigh distribution is$$f(x;\sigma) = \frac{x}{\sigma^2} e^{-x^2/(2\sigma^2)}, \quad x \geq 0,$$where $\sigma$ is the scale ...
Xi'an's user avatar
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1 vote
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In this a form of selection bias?

Your sampling will no longer be random, given that you select samples on a criteria you do not mention, so in this sense you would have selection bias (but once we said that, we still have to consider ...
J-J-J's user avatar
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6 votes
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Proof of Rejection Sampling: Flawed reasoning about continuous random variables

To quote from our book Monte Carlo Statistical Methods, the most straightforward way of validating Accept-Reject sampling is to see it as simulating uniformly on a set $B$ until the simulation belongs ...
Xi'an's user avatar
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3 votes

Are bootstrapped samples considered to be coming from the same distribution as the original sample?

Are bootstrapped samples considered to be coming from the same distribution as the original sample? NOT QUITE In the simulation below, I draw 50 observations from a standard normal distribution. <...
Dave's user avatar
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1 vote

Should sum of sample weights always be equal to the target population

In addition to trimming, it's quite possible with cluster sampling or multistage sampling that the target population size is not known. You might not know the size of clusters you don't sample. The ...
Thomas Lumley's user avatar
2 votes

Pooling samples ahead of analysis - valid?

A few points beyond what @PBulls addressed (+1) in another answer. All of the cells you are examining come from a single donor, and thus any inferences you make will be restricted to that donor. Some ...
EdM's user avatar
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5 votes
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Piecewise continuous power law distribution sampling

You can see this distribution as a mixture of two power law distributions, $$f(x)=\alpha f_1(x) + (1-\alpha) f_2(x)$$ with $$f_1(x)=\frac{𝑥^{−a_1}\mathbb I_{x_1\le x\le \tilde x}} {\underbrace{\int_{...
Xi'an's user avatar
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2 votes
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In Bayesian Linear Regression, do I need to take multiple samples of the Posterior for prediction?

You want the posterior predictive for $y$, which will be given as $p(y^{rep}|y)=\int p(y^{rep}|\beta,y)p(\beta|y)=\int p(y^{rep}|\beta)p(\beta|y)$. This suggests the following procedure for generating ...
user1848065's user avatar
4 votes

Pooling samples ahead of analysis - valid?

I'm going to sidestep the (very valid!) concerns raised over technical vs. biological replication - if you're working with a cell line or inbred animals one might argue that you can only ever do ...
PBulls's user avatar
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How to treat age-eligibility thresholds in household surveys (e.g. HRS)?

The consideration of those who are under the age threshold in household surveys such as the Health and Retirement Study (HRS) is contingent upon the particular research objectives and the population ...
Robert Long's user avatar

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