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Questions tagged [posterior]

In Bayesian statistics, the term 'posterior' refers to the probability distribution of a parameter conditioned on the observed data.

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I am working on a Bayesian hierarchical model of a plant physiological process written in Stan. Basically it can be broken down to a multilevel piecewise regression model with a species-specific ...
Roman Link's user avatar
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Background Consider the following recursive Bayesian classifier \begin{equation} p_{t}(c)=\frac{\ell(y_t\mid c)p_{t-1}(c)}{\sum_{\nu=1}^C \ell(y_t\mid \nu)p_{t-1}(\nu)}, \qquad c=1,\dots,C \tag{1} \...
matteogost's user avatar
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Bayesian updating is sometimes described by the following equation: \begin{equation*} \text{Posterior}=\sigma \times \text{Signal}+(1-\sigma )\times \text{Prior} \end{equation*} This expression treats ...
Max201019's user avatar
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Suppose $X$ is a random variable taking values in $\{-1, 0, 1\}$. Say that a priori I know nothing about $X$ so my prior distribution for $X$ is $\Pr(X = x) = 1/3 \quad(x = -1, 0, 1)$. Now suppose I ...
user475539's user avatar
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I’m fitting a mixture model in Stan to strictly positive data. Each component distribution has a mean that can be expressed by some summation of a and b. (a and b are two “factor” parameters shared ...
brightlilac's user avatar
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Low Acceptance Rate in Independent Metropolis-Hastings with Jeffreys Prior Model Specification Implementing an Independent Metropolis-Hastings sampler for: Likelihood: $$ f_X(x \mid \theta) \propto ...
Filippooo's user avatar
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I am trying to estimate a posterior distribution and specifically its entropy using a Sequential Monte Carlo (SMC) sampler. Given a prior $p(x)$ and a likelihood $p(y|x)$ I am using SMC with adaptive ...
maxlman's user avatar
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5 votes
2 answers
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I am practicing some concepts from my graduate stats class and trying to derive the Bayes rule for the squared loss function $L(\theta,a)=(\theta-a)^2$. I have a Laplace distribution with location ...
OzymandiusBlorg's user avatar
1 vote
2 answers
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There is a similar question that was asked here: Gaussian processes: posterior vs. predictive distributions but it never received any attention and so I am re-asking the question although the emphasis ...
John Smith's user avatar
3 votes
1 answer
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Using a Dirichlet prior and a multinomial likelihood model, one can derive the posterior distribution for the estimation of the frequency of discrete events. A technique of pseudocounts can be applied ...
EngineerMathlover's user avatar
6 votes
6 answers
965 views

Inspired by this twitter thread, posting this question: I have two children, (at least) one of whom is a boy born on a Tuesday what is the probability that both children are boys? Via Joel Grus, ...
Estimate the estimators's user avatar
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I have got a question that I am not sure how to answer on it, and I would like to get some clarification, or to point me out where is the problem in my understanding. We got a logistic regression ...
Tomas's user avatar
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4 votes
3 answers
393 views

This question is around clarification for whether the posterior distribution and posterior predictive distribution can be used to create an interval estimate for a quantile. Consider the following ...
John Smith's user avatar
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Currently i'm estimating HR splines using mgcv::gam::coxph. My spline is nonlinear and has one turn, so i'd like to divide my spline into two sections given the turn and get conditional estimates for ...
Tom's user avatar
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Question: I am performing importance sampling (IS) for a Bayesian inference problem with the following setup: 1. Data and Model My data has ( D = 1300 ) dimensions. The log-likelihood, $ \log p(x \...
malavika v vasist's user avatar

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