All Questions
Tagged with prior beta-distribution
36
questions
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Does the beta negative binomial (BNB) distribution have a conjugate prior?
BNB distribution is constructed using negative binomial and beta distributions, which are both exponential family, so my guess would be yes, there shoudl exist a conjugate prior in theory. But what is ...
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139
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Using a Generalized Beta Distribution of the Second Kind as a Prior in Stan Linear Regression
So I'm considering a simple linear regression model with $p = 1$ predictor $$y = \beta x + \epsilon$$ where $\epsilon \sim N(0,\sigma^2)$. I want to use a generalised beta distribution of the second ...
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141
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References for the conjugate prior to the beta distribution? [duplicate]
The Wikipedia article about "Conjugate Prior" has a table containing information about Likelihood Distributions with their Conjugate Priors.
In the "Continuous Likelihood" table, ...
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Beta distribution equivalence with two redondant parameters [duplicate]
context
In Factor graphs on discrete variables, the parameters are contained in factors associated each with a subset of the random variables in the system. Each factor provides a different positive ...
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81
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Can I use a Prior with Simulated data?
I have a prior about some proportion that follows a Beta distribution. Unfortunately, I do not have (yet) observed data but I was offered a thousand simulated datasets.
Each dataset comes from ...
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139
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What distribution would make a good hyper-prior for a Beta distribution parameterized by mean and sample size?
I have a model which includes a Beta distribution and I am looking for guidance on how to parameterize a hyper-prior for it. For example, this post uses a Beta parameterized with a mean and ...
- 1,207
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255
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Application of spike and slab for sampling from posterior distribution (bernoulli and beta)
I think the gamma N term in the first equation relates to the spike and prior. However, I am unsure what the rhs of the first is used for? Further, I am unsure what the pie term of the second equation ...
- 103
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195
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Beta distribution with a priors as Uniform and Pareto Distribution
I am working on a bayesian programming problem which involves a Beta Posterior, which has mean (location) parameter coming from Uniform Distribution [U(0,1)] and concentration (kappa) coming from ...
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How can I choose how confident my beta distributed bayesian prior should be?
I am new to Bayesian statistics, and would appreciate help understanding the Prior.
I want to combine a small national dataset with a prior from very large international studies, to give a posterior ...
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4
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Update beta distributed prior with data that is a probability
In my experience with Bayesian statistics, beta distributions are typically used to estimate the posterior for parameter, $p$, of a binomial distribution that has been used to generate some data. But ...
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2
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319
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Bayesian priors and probability distributions
Book "Bayesian Statistics the Fun Way: Understanding Statistics and Probability
with Star Wars, Lego, and Rubber Ducks", chapter 9 "Bayesian priors and working
with probability ...
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2
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1
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193
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Parameters of beta distribution with a given HDI [duplicate]
Is there some way to calculate the parameters of a beta distribution, if the highest density interval is known. That is, given $a,b,x$ I want to have a beta distribution such that the probability of ...
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156
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Why are $\mathbb{E}( \ln(x))$ and $\mathbb{E} ( \ln(1 - x))$ reasonable descriptions of knowledge about a beta distribution?
The max entropy philosophy states that given some constraints on the prior, we should choose the prior that is maximum entropy subject to those constraints.
I know that the Beta($\alpha, \beta$) is ...
- 221
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Why are beta distributions commonly chosen for priors? [duplicate]
Is there any specific reason why a Beta distribution would be chosen as a prior, other than that it is conjugate for the Binomial?
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Geometric distribution with a capped number of trials - finding expectation and prior predictive distribution
So I am modeling a random variable which follows a geometric distribution with probability $\theta$ except that the total number of trials is capped at some value $n$. I.e., the probability mass ...
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