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What does "Parameters are fixed and data vary" in frequentists' term and "Parameters vary and data are fixed" in Bayesians' term exactly mean?

answered Oct 11, 2020 at 9:17

6 votes

In Bayesian inference, why is p(D) sometimes called "the evidence"?

answered Feb 23, 2020 at 4:00

4 votes

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What is the intuitive meaning of these statements in the context Bayesian prior and posterior?

answered Feb 22, 2020 at 13:22

4 votes

What's the big deal with normalization constants in Bayesian inference?

answered Sep 20, 2019 at 17:14

4 votes

Jensen Shannon Divergence vs Kullback-Leibler Divergence?

answered Jun 5, 2021 at 21:46

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On the optimal distribution for importance sampling

answered Dec 31, 2021 at 19:53

2 votes

Models for describing cluster change over time

answered Feb 25, 2022 at 6:39

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distance between regression models

answered Dec 31, 2021 at 4:53

2 votes

What is statistic in statistics?

answered Sep 23, 2019 at 16:14

1 vote

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How are higher level posteriors modeled in a hierarchical Bayesian model?

answered Sep 24, 2019 at 7:09

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Finding the posterior distribution given an improper prior

answered Sep 21, 2019 at 6:49

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What does it mean to have assymetric proposal distributions when coding the Metropolis-Hastings Algorithm?

answered Sep 22, 2019 at 3:30

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Why do we draw parameters to draw from a marginal distribution that does not contain the parameters?

answered Oct 6, 2019 at 19:55

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Would a posterior distribution with a flat prior look identical to the likelihood?

answered Feb 4, 2020 at 7:13

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Bayesian hypothesis test to compare theta >= 1 vs. theta < 1

answered Feb 7, 2020 at 18:29

1 vote

Problems with using Gibbs Sampling for Bayesian DAGs

answered Feb 11, 2020 at 8:53

1 vote

What exactly does the term "inverse probability" mean?

answered Oct 22, 2020 at 0:45

1 vote

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Formal arguments for why an asymmetric f-divergence might be favourable to a symmetric one in analyzing importance sampling

answered Jun 5, 2021 at 1:37

1 vote

How to use the MCMC method for multivariate distributions?

answered Feb 23, 2020 at 4:11

1 vote

Bayesian comparison of differing model size

answered Feb 29, 2020 at 14:40

1 vote

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Bayesian model: binomial(s) conditional on Poisson

answered Mar 3, 2020 at 9:20

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On distributions over orthonormal sets: existing families, construction, and simulation

answered Jan 30, 2022 at 21:31

1 vote

Is it fair to say that most real-life distributions have finite variance?

answered Aug 23 at 2:07

1 vote

Famous easy to understand examples of a confounding variable invalidating a study

answered Dec 7 at 22:38

0 votes

Statistical tests when sample size is 1

answered Dec 7 at 22:50

0 votes

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Beta-Binomial Gibbs Sampler

answered Feb 13, 2022 at 19:03

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How should I transform non-negative data including zeros?

answered Oct 20, 2022 at 16:28

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Calculating optimal number of bins in a histogram

answered Dec 31, 2021 at 7:54

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Determining an optimal discretization of data from a continuous distribution

answered Dec 31, 2021 at 8:08

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When MAP beats ADVI

answered Mar 30, 2020 at 4:51

Stack Exchange Network

32 Answers

What does "Parameters are fixed and data vary" in frequentists' term and "Parameters vary and data are fixed" in Bayesians' term exactly mean?

In Bayesian inference, why is p(D) sometimes called "the evidence"?

What is the intuitive meaning of these statements in the context Bayesian prior and posterior?

What's the big deal with normalization constants in Bayesian inference?

Jensen Shannon Divergence vs Kullback-Leibler Divergence?

On the optimal distribution for importance sampling

Models for describing cluster change over time

distance between regression models

What is statistic in statistics?

How are higher level posteriors modeled in a hierarchical Bayesian model?

Finding the posterior distribution given an improper prior

What does it mean to have assymetric proposal distributions when coding the Metropolis-Hastings Algorithm?

Why do we draw parameters to draw from a marginal distribution that does not contain the parameters?

Would a posterior distribution with a flat prior look identical to the likelihood?

Bayesian hypothesis test to compare theta >= 1 vs. theta < 1

Problems with using Gibbs Sampling for Bayesian DAGs

What exactly does the term "inverse probability" mean?

Formal arguments for why an asymmetric f-divergence might be favourable to a symmetric one in analyzing importance sampling

How to use the MCMC method for multivariate distributions?

Bayesian comparison of differing model size

Bayesian model: binomial(s) conditional on Poisson

On distributions over orthonormal sets: existing families, construction, and simulation

Is it fair to say that most real-life distributions have finite variance?

Famous easy to understand examples of a confounding variable invalidating a study

Statistical tests when sample size is 1

Beta-Binomial Gibbs Sampler

How should I transform non-negative data including zeros?

Calculating optimal number of bins in a histogram

Determining an optimal discretization of data from a continuous distribution

When MAP beats ADVI